Hestia Domain — Features

Hestia — Culinary Intelligence and Smart Home Platform

Hestia (the Greek goddess of the hearth and home — the fire that is the center of domestic life) is a comprehensive culinary arts and food intelligence platform. It covers recipe management and intelligent parsing, guided cooking with voice control, deep ingredient science, nutritional analysis with bioavailability modeling, meal planning, pantry inventory management, smart kitchen IoT integration, culinary heritage preservation, sustainability tracking, culinary education, professional kitchen tools, social cooking, and AI/ML-driven culinary intelligence.

Every library in libs/hestia/ corresponds to a specific capability described below.

Domain boundary: Hestia owns consumer and home culinary intelligence. The adjacent Annapurna domain owns restaurant and commercial food-service operations. Hestia may provide recipe, nutrition, and smart kitchen data to Annapurna, but commercial service workflows (point of sale, franchise management, commercial kitchen compliance at scale) belong to Annapurna.

1. Core Platform#

@hestia/core is the foundation library for the entire Hestia ecosystem. It defines the canonical types and data structures that every other Hestia library shares — from the Recipe entity through the event bus to the authorization model. Because all libraries declare @hestia/core as a peer dependency rather than a direct one, the consuming application controls the single installed copy, preventing version conflicts.

• Recipe entity: Full recipe representation schema including structured ingredients, step-by-step instructions, timing (total, active, per-step), equipment requirements, difficulty classification, yield, and multi-tag metadata for cuisine, dietary category, and meal type.
• Ingredient entity: Master ingredient database entries with nutritional data linkage to USDA FoodData Central, allergen flags, standard category, and measurement conversion data.
• Cooking session entity: Represents an active guided cooking session — tracking progress through steps, timer states, modifications, and outcomes.
• Comprehensive type system: TypeScript enums and types covering measurement units (24 across US/metric volume, US/metric weight, and informal units), cooking methods (35 total — roast, braise, sauté, steam, poach, ferment, and more), dietary restriction types (vegan, vegetarian, keto, paleo, kosher, halal, gluten-free, and more), allergen types aligned with EU + US allergen regulation, a cuisine taxonomy of named world cuisines grouped by region and nested into sub-cuisines, meal categories, difficulty levels, temperature units, texture profiles, and flavor profiles (sweet, salty, sour, bitter, umami, spicy).
• Domain event bus: Ten domain events for cross-module communication — recipe.created, recipe.updated, recipe.cooked, recipe.rated, ingredient.added, meal.planned, shopping_list.generated, pantry.updated, cooking_session.started, and cooking_session.completed — allowing modules to react to activity from other modules without direct coupling.
• Event store: Complete event history for domain events, enabling event sourcing and audit trails.
• Database schema: PostgreSQL with full-text search indexes, recipes table, ingredients master table, recipe-ingredients junction, users table with dietary preferences, meal plan calendar, pantry items, shopping lists, equipment inventory, cooking sessions, and flavor compound data.

2. Recipe Management#

Recipe Data Model (@hestia/recipes)#

The recipe library provides the richest data model in the domain. Every recipe is not just a list of ingredients and steps — it carries timing breakdowns that distinguish "hands-on" time from passive waiting, difficulty ratings calibrated against specific technique complexity criteria, and full multi-tag classification that enables rich multi-facet filtering.

• Rich recipe structure: Full recipe representation with structured ingredient lists, step-by-step instructions with timing annotations, equipment requirements, difficulty rating, cuisine tags, dietary tags, and user-facing metadata.
• Ingredient linking: Each recipe ingredient is linked to the master ingredient database entry — enabling automatic nutrition calculation, allergen detection, and substitution lookups without manual annotation.
• Equipment tracking: Required equipment listed per recipe, enabling feasibility checking against the user's registered equipment inventory before beginning.
• Timing breakdown: Total time, active cooking time (time when the cook must be present), and per-step timing for accurate cooking session planning — distinguishing a 2-hour recipe that requires only 30 minutes of attention from one requiring 2 hours of constant work.
• Difficulty rating: Calibrated difficulty classification based on technique complexity, timing precision requirements, ingredient accessibility, and number of simultaneous operations.
• Multi-tag classification: Each recipe tagged with cuisine tradition, dietary categories, meal type, cooking method, primary ingredient, season, and occasion — enabling rich multi-facet filtering.

Recipe Parsing and Import#

Hestia can ingest recipes from almost any source format — pasted blog text, website URLs, photograph of a handwritten card, or structured JSON-LD — and convert them into the same structured data model. This means a user's grandmother's recipe scrawled on an index card and a professional recipe from a restaurant website end up in the same queryable format.

• Text parsing: Extraction of structured recipe data from unstructured plain text using pattern matching and NLP — converting a pasted recipe blog post into a fully structured recipe entity.
• URL import: Recipe import from web URLs by parsing Recipe Schema.org JSON-LD structured data embedded in recipe websites, with fallback HTML parsing for sites without Schema.org markup.
• Image-based extraction: Recipe extraction from photographs of handwritten recipe cards or printed cookbooks — OCR followed by structured extraction, preserving family recipes in digital form.
• Multi-format import/export: Import from Recipe Schema.org JSON-LD, Markdown, and plain text; export to JSON-LD, Markdown, and plain text for sharing, archival, and cross-platform use.

Recipe Scaling and Conversion#

Scaling is harder than it looks — some ingredients are linear (double the beef when doubling portions), but others are not (leavening agents, salt, yeast, and spices all require non-proportional adjustment or the result will be inedible). Hestia handles these special cases explicitly.

• Serving size scaling: Proportional ingredient adjustment for different serving sizes with intelligent rounding — converting 2.5 eggs to 3 eggs with a note to use a slightly smaller egg.
• Unit conversion: Automatic conversion between US customary (tsp, tbsp, cup, fl oz, oz, lb) and metric (ml, dl, L, g, kg) measurement systems with ingredient-specific density factors.
• Non-linear scaling: Special handling for ingredients that do not scale linearly — leavening agents (baking powder/soda), salt, spices, and yeast all require scaling adjustments rather than direct multiplication.
• Informal unit support: Handle informal measurement units common in traditional recipes — "a pinch of salt," "a dash of Worcestershire," "a sprig of thyme," "a clove of garlic," "a bunch of parsley" — converting to precise quantities where needed.

Recipe Versioning and Collaboration#

Recipes evolve over time — a cook tries a dairy-free variation, a kitchen team refines a dish over months, a family maintains a canonical version while letting members add their own twists. The versioning system treats recipe development with the same rigor as software development: full history, branching, merging, and attribution.

• Version history: Complete modification history with diff tracking for every recipe change — who changed what and when, with the ability to view and restore any previous version.
• Branching: Create a recipe branch for experimental variations (e.g., "the dairy-free version") without modifying the original recipe.
• Merge support: Merge recipe branches back into the main version with conflict resolution when both branches have been modified.
• Collaborative editing: Multi-user recipe development with attribution tracking per contribution — critical for culinary teams and shared family recipe books.

Recipe Search and Collections#

• Full-text search: Search across recipe names, descriptions, ingredient lists, and instruction text with relevance ranking.
• Multi-facet filtering: Filter by cuisine (across the full regional cuisine taxonomy), dietary restriction, cooking method, specific ingredient, total time, active time, difficulty, and equipment required.
• Recipe collections: User-defined collections and digital cookbooks for personal organization — "Weeknight favorites," "Dinner party," "My grandmother's recipes."
• Auto-generated collections: Automatically curated seasonal (spring salads, winter soups), thematic (5-ingredient meals, one-pot dishes), and trending groupings.

3. Guided Cooking#

Step-by-Step Guidance (@hestia/cooking)#

The cooking module turns a static recipe into a live, interactive session. Its most powerful feature is multi-recipe coordination: when cooking a full meal, the system analyzes all recipe steps together and produces a single interleaved timeline — telling you when to start the rice so it finishes at the same time as the protein.

• Interactive cooking sessions: Step-through cooking sessions with progress tracking — each step displays instructions, timing, technique guidance, and the option to pause, repeat, or skip.
• Step reordering across multiple recipes: When cooking multiple recipes simultaneously for a meal, the system analyzes all steps across all recipes and generates an optimal interleaved cooking sequence — telling you when to start the rice to have it finish at the same time as the protein.
• Real-time in-session modifications: Modify recipe scaling or ingredient substitutions during an active cooking session without losing progress.
• Session completion tracking: Progress percentage and estimated time remaining updated dynamically as steps are completed, accounting for actual elapsed time vs. planned timing.

Timer Management#

Managing multiple simultaneous cooking timers is one of the hardest coordination problems in a busy kitchen. Hestia models timers as first-class objects with distinct states — relative timers that start when a step is acknowledged, absolute target-time timers that work backwards from a desired finish time, and conflict detection that warns when two timers will require simultaneous attention.

• Multiple concurrent timers: Manage many independent cooking timers simultaneously — crucial for complex meals with multiple dishes at different stages.
• Relative timers: Timers that start automatically when a cooking step is acknowledged as begun — "set a 15-minute timer" happens without manual input.
• Absolute timers: Target-time timers calculated backward from a desired completion time — "I need dinner on the table at 7:30" produces a timeline of when each task must begin.
• Conflict detection: Detection of overlapping timers that would require the cook's simultaneous attention — alerting before the situation arises.
• Alert notifications: Audio and visual alerts when timers complete, with distinct sounds per timer to differentiate by sound alone (without looking at the device).

Voice Interface#

Voice control is not a convenience feature in a kitchen — it is a safety and hygiene necessity when hands are covered in raw chicken or sticky dough. Every command that matters during an active cooking session is reachable by voice.

• Hands-free control: Voice command recognition for cooking control — critical when hands are covered in flour or raw chicken.
• Timer voice commands: Start, stop, check status, and extend timers by voice ("start a 10-minute timer for the pasta," "how much time is left on the chicken?").
• Step navigation: Navigate forward ("next step") and backward ("go back") through recipe steps by voice.
• Unit conversion queries: Ask for unit conversions verbally during cooking ("how many tablespoons is 45 milliliters?").
• Substitution lookups: Voice-activated ingredient substitution queries while cooking ("what can I use instead of buttermilk?").

Doneness and Technique Guidance#

• Temperature guides: USDA-recommended internal temperature targets for proteins by doneness level — 145°F for whole beef, 160°F for ground beef, 165°F for all poultry, 145°F for pork with 3-minute rest.
• Visual doneness guides: Visual and textual doneness indicators for ingredients where temperature measurement is impractical — golden-brown crust, clear juices, firm texture, spring-back tests.
• Resting time calculations: Post-cooking resting time recommendations accounting for carryover cooking — a thick steak can rise 5–10°F after being removed from heat, making resting essential for accurate doneness.
• Technique library: Detailed instructions for fundamental cooking methods (sautéing, braising, poaching, roasting, grilling, steaming) with skill-level appropriate guidance and common mistake prevention.
• Video references: Links to video demonstrations for complex techniques where written instructions are insufficient (e.g., julienning, making hollandaise, laminating pastry dough).

Session Logging#

• Session recording: Complete cooking session data capture including actual elapsed time vs. planned, notes taken, modifications made, and timer history.
• Outcome tracking: Record cooking outcomes — success rating, issues encountered, flavor notes, what to change next time — creating a personal cooking journal.
• Skill progression tracking: Cooking history feeds into skill tracking, recording which techniques have been practiced and how frequently.

4. Ingredient Intelligence#

Master Ingredient Database (@hestia/ingredients)#

The ingredient database is deeper than a simple lookup table. Each entry carries hierarchical categorization, regional name aliases, storage guidance, weight-to-volume conversion factors, and links to flavor compound profiles. This depth is what enables smart substitution, pairing suggestions, and accurate nutrition calculation elsewhere in the platform.

• Comprehensive catalog: Extensive ingredient database with hierarchical categorization (produce → vegetables → root vegetables → carrots), descriptions, multiple regional name variants, and standard measurement conversions.
• Aliases and regional variations: Regional name variations and common aliases — aubergine/eggplant, coriander/cilantro, courgette/zucchini — ensuring search works regardless of culinary tradition.
• Measurement conversions: Weight-to-volume conversions per ingredient accounting for density — 1 cup of all-purpose flour weighs very differently than 1 cup of water or 1 cup of honey.
• Category organization: Hierarchical ingredient categorization (produce, dairy, protein, grain, spice, condiment, baking, pantry staple) for pantry organization and recipe filtering.

Flavor Compound Science#

Hestia's flavor intelligence is based on the same biochemical reality that underlies the "Flavor Bible" approach — ingredients that share volatile chemical compounds tend to taste harmonious together. The flavor compound database maps specific molecules to specific ingredients, enabling computational flavor pairing at a scale and precision that no printed reference can match.

• Flavor compound database: Database of volatile and non-volatile flavor compounds mapped to specific ingredients — e.g., linalool (floral, citrus) in coriander, eugenol (clove, spice) in basil, ethyl butanoate (fruity, pineapple) in strawberries.
• Flavor families: Compound classification into flavor families (fruity, floral, earthy, umami, Maillard reaction products, sulfurous, fatty, herbal) based on chemical structural relationships.
• Per-ingredient flavor profiles: Compound profiles showing which compounds are present and in what concentrations — enabling compound-based flavor pairing analysis.

Flavor Pairing#

• Chemical compatibility pairing: Flavor pairing suggestions based on shared volatile compound overlap analysis — the Flavor Bible approach made computational and scalable. Ingredients sharing many volatile compounds tend to taste harmonious together.
• Cultural affinity pairing: Traditional culinary pairing databases capturing centuries of established ingredient combinations from specific cuisine traditions — the cultural wisdom alongside the chemistry.
• Compatibility scoring: Numeric pairing scores combining chemical compatibility (volatile compound overlap) and cultural context (traditional usage frequency) into an actionable compatibility rating.
• Novel combination discovery: Surface non-obvious ingredient pairings through compound analysis — finding that coffee and beef (both high in pyrazines) work together, or that strawberry and black pepper complement each other.

Ingredient Substitution#

Substitution is one of the most contextual problems in cooking. Replacing tarragon in a salad calls for something with similar anise-y flavor notes; replacing eggs in a cake requires understanding which egg role (binding, leavening, moisture) the specific recipe is relying on.

• Flavor-matched substitutions: Replacement suggestions prioritized by flavor profile similarity — when a recipe calls for tarragon and it's unavailable, suggest alternatives in order of flavor similarity.
• Texture matching: Substitutions that account for textural role and cooking behavior differences — replacing eggs in baking requires different substitutes for their binding, leavening, and moisture roles.
• Dietary substitutions: Tested alternatives for common allergens and dietary restrictions — dairy-free milk alternatives with guidance on how fat and protein content differences affect cooking outcomes; gluten-free flour blends with binding agent additions; egg substitutes with notes on which applications they suit.

Seasonality#

• Regional availability: Ingredient availability tracking by season and geographic region — identifying ingredients that are in season in the user's region.
• Peak season data: Peak flavor and nutrition windows for seasonal produce — tomatoes in August taste fundamentally different from tomatoes in January, and the platform communicates this.
• Seasonal recommendations: Recipe and ingredient suggestions aligned with current seasonal availability, reducing food miles and cost while maximizing flavor.

5. Nutritional Analysis#

Recipe Nutrition Calculation (@hestia/nutrition)#

Nutrition calculation in Hestia goes well beyond label math. Cooking method effects are modeled (boiling leaches water-soluble vitamins; roasting concentrates sugars), and all nutritional data is traceable to USDA FoodData Central identifiers for accuracy and auditability.

• Per-serving analysis: Complete nutritional breakdown per serving — calories, total fat, saturated fat, trans fat, cholesterol, sodium, total carbohydrates, dietary fiber, total sugars, added sugars, protein, and 20+ micronutrients (vitamins A, C, D, E, K, B-vitamins, calcium, iron, potassium, zinc, and more).
• Per-recipe totals: Total recipe nutritional content for batch cooking and meal prep planning.
• Cooking method effects: Nutrition adjustments for cooking method impact — boiling reduces water-soluble vitamins; frying adds fat; roasting concentrates sugars; heat increases lycopene bioavailability in tomatoes.
• USDA FoodData Central integration: Nutritional data referenced against USDA FoodData Central (FDC) identifiers for traceability and accuracy.

Bioavailability Modeling#

Bioavailability is the fraction of an ingested nutrient that is actually absorbed into the bloodstream and is available for use. Raw nutritional content and actual absorption can differ dramatically — non-heme iron from spinach has 2–20% absorption, while heme iron from beef reaches 15–35%. Hestia models these differences explicitly, giving users a more accurate picture of what their bodies actually receive from a meal.

• Nutrient absorption efficiency: Model actual nutrient absorption based on preparation method, food matrix, and meal composition — non-heme iron from plant sources has only 2–20% absorption vs. 15–35% for heme iron from meat.
• Synergistic nutrient interactions: Model positive interactions that increase bioavailability — vitamin C dramatically increases non-heme iron absorption; fat increases fat-soluble vitamin (A, D, E, K) absorption; black pepper (piperine) increases curcumin absorption ~20-fold.
• Inhibitory nutrient interactions: Model negative interactions that reduce bioavailability — phytates in whole grains reduce zinc and iron absorption; calcium reduces iron absorption when consumed together; tannins reduce iron absorption.
• Individual factors: Adjust bioavailability estimates for individual characteristics — people with iron deficiency absorb more iron; postmenopausal women absorb more calcium.

Dietary Framework Management#

• Framework support: Comprehensive support for vegetarian (lacto-ovo, lacto, ovo), vegan, ketogenic (<20g net carbs, high fat), paleo (no grains/legumes/dairy), Mediterranean (high olive oil, fish, vegetables, whole grains), DASH (Dietary Approaches to Stop Hypertension), low-FODMAP (for IBS), carnivore, and fully custom diet frameworks.
• Compliance checking: Automatic recipe and meal plan compliance verification against active dietary frameworks — flagging violations with specific ingredient or macro explanations.
• Medical diets: Renal diet (potassium and phosphorus restricted), diabetic diet (glycemic index consideration, carbohydrate counting), cardiac diet (saturated fat and sodium restricted), and elimination diet protocols.

Allergen Detection#

Hidden allergens are a real safety issue — "lecithin" often means soy lecithin, "hydrolyzed vegetable protein" may contain wheat or soy, and trace cross-contact can trigger reactions in severely allergic people. Hestia's allergen detection operates at the ingredient-name level, not just at the obvious top-level tag.

• Major allergen groups: Detection of the 14 major allergens per EU regulation and Big 9 per US FALCPA: dairy, eggs, fish, shellfish, tree nuts, peanuts, wheat/gluten, soy, sesame.
• Hidden allergen detection: Identification of allergens in processed ingredient names — "lecithin" can mean soy lecithin, "casein" means dairy protein, "hydrolyzed vegetable protein" may contain soy or wheat.
• Cross-contamination warnings: Advisory notices for potential cross-contact in shared kitchen environments — relevant for people with severe allergies where trace amounts are clinically significant.

Nutrition Goals#

• Personalized targets: Nutrition targets calculated from age, sex, height, weight, activity level, and health goals using established formulas (Mifflin-St Jeor for BMR, TDEE multipliers for activity).
• Progress tracking: Daily, weekly, and long-term progress visualization toward nutrition goals with trend analysis.
• Deficit and surplus alerting: Notifications when macro or micronutrient intake is significantly below or above targets, with context about why it matters.

6. Meal Planning#

Calendar Planning (@hestia/meal-planning)#

• Weekly and monthly calendar views: Drag-and-drop meal assignment across calendar views — planning breakfast, lunch, dinner, and snacks for every day of the week or month.
• Recurring meal patterns: Repeating meal schedule patterns for consistent household routines — "taco Tuesday" or "fish Friday" become automatic.
• Leftover integration: Track planned leftovers from one meal and automatically integrate them as ingredients in subsequent meal slots, reducing food waste.

Household Management#

Multi-person households are the common case, not the exception. Hestia models each household member's dietary restrictions and portion preferences separately, then finds meal plans that satisfy everyone simultaneously rather than forcing a lowest-common-denominator compromise.

• Multi-person household profiles: Individual dietary preferences, allergen profiles, and nutrition goals per household member — the meal plan satisfies everyone simultaneously.
• Portion size adjustment: Automatic recipe scaling for household size and individual serving preferences — different portions for adults and children.
• Dietary accommodation: Automatic filtering of meal suggestions to satisfy all household members' restrictions simultaneously.

Meal Suggestions and Budgeting#

• Intelligent meal suggestions: Recommendations based on pantry contents (prioritizing ingredients about to expire), seasonal ingredients, stated taste preferences, nutritional goals, and recent meal history (avoiding repetition).
• Budget tracking: Per-serving and per-meal cost calculations with weekly and monthly budget targets — making nutrition-conscious eating accessible regardless of budget.
• Cost optimization: Meal suggestions that minimize grocery spending while meeting nutritional targets — optimizing for cost-per-nutrient rather than just cost.

Batch Cooking and Events#

• Batch cooking planning: Session planning that maximizes efficiency by identifying shared prep steps across multiple recipes — all chopping done together, all roasting done together.
• Freezer-friendly scheduling: Make-ahead and freezer-friendly meal scheduling — identifying which planned meals can be prepared days in advance and frozen for busy days.
• Event meal planning: Recipe scaling and dietary accommodation for dinner parties, holiday meals, and catering situations with specific guest count and dietary requirement management.

7. Pantry and Kitchen Inventory#

Pantry Inventory (@hestia/pantry)#

The pantry module manages the full lifecycle of food inventory — from the moment an item is scanned in at purchase through its storage location, expiration date, and eventual use or disposal. FIFO rotation guidance ensures older stock is used before newer stock, reducing waste.

• Item tracking: Complete pantry inventory with quantities, storage locations (shelf, cabinet, refrigerator drawer, freezer), purchase dates, and categories.
• Barcode scanning: Barcode scanning for rapid item addition — scan a product barcode to automatically identify the item and pre-fill nutrition and allergen data. OCR receipt processing for batch pantry updates from grocery receipts.
• Expiration monitoring: Configurable expiration date alerts with FIFO (First In, First Out) rotation guidance — using older stock before newer stock.
• Equipment inventory: Kitchen equipment tracking (stand mixer, pressure cooker, immersion blender, etc.) with maintenance schedules and usage frequency tracking for feasibility checking.

Shopping#

• Automatic shopping list generation: Shopping lists generated automatically from meal plans (what's needed for this week's meals that's not in the pantry) combined with pantry restock needs (items that have fallen below minimum quantity).
• Store aisle organization: Shopping lists organized by store aisle for efficient in-store navigation — grouping produce, then dairy, then meat, etc.
• Price tracking: Price history tracking per item and store with sale notification when frequently purchased items are discounted.
• Grocery store mapping: Store-specific aisle layouts for optimized shopping routes in regular stores.

8. Smart Kitchen IoT#

Device Management (@hestia/smart-kitchen)#

The smart kitchen module abstracts over the fragmented landscape of kitchen IoT devices. Rather than requiring a separate integration per brand, it defines capability-based adapter interfaces that any smart oven, sous vide circulator, or connected thermometer can implement. The automation engine then builds event- driven workflows on top of these adapters.

• Device registration and discovery: A device registry handles registration, network discovery, command queueing, and lifecycle management for kitchen IoT devices. Devices are modeled by capability and category rather than by brand.
• Cooking device integration: Brand-agnostic adapters and controllers for smart ovens (with cooking modes and program control), sous vide circulators (with multi-bag scheduling), and pressure cookers (with pressure levels and release types).
• Sensor integration: Adapters for connected temperature probes with doneness prediction, and smart scales with baker's-percentage and nutrition-estimation support.
• Smart appliances: Adapters and controllers for connected refrigerators (zones, expiration alerts, recipe suggestions), coffee machines (coffee type and grind level), and cooktops (with safety checks).

Automation and Orchestration#

• Rule-based automation: Automation workflows triggered by cooking events ("when the oven reaches 375°F, send a notification"), sensor readings ("when internal temperature reaches 160°F, alert"), and timer completions.
• Multi-device orchestration: Coordination of multiple appliances for complex meal preparation — automatically starting the oven preheating when the guided cooking session begins.
• Cooking scenes: Predefined scenarios combining multiple devices — "Sunday roast" scene sets oven temperature, starts the range hood, and sets the warming drawer simultaneously.

9. Culinary Heritage Preservation#

Preserving culinary traditions, family recipes, and food culture for future generations (@hestia/heritage). Much of the world's culinary knowledge exists only in oral tradition — grandmothers who have never written a recipe down, but cook from memory and feel. Hestia provides the tools to capture, structure, and preserve that knowledge before it is lost.

• Family recipe digitization: Digitize handwritten or orally transmitted family recipes with photograph preservation, original author attribution, and provenance story capture — preserving not just the recipe but its history.
• Oral history recording: Audio and video recording of cooking-related oral histories (grandmothers teaching their techniques, family cooking stories) with automatic transcription for searchability.
• Regional archive: Catalog of regional cuisine traditions with geographic mapping, historical context, and the cultural and economic factors that shaped each cuisine.
• Food history research: Research-grade food history content with timeline visualization showing the evolution of cuisines and cultural influence mapping — how ingredients and techniques traveled between cultures.
• Community contribution: Moderated community contributions to the heritage preservation archive with cultural sensitivity guidelines — enabling communities to document their own food traditions.

10. Sustainability and Ethical Living#

Environmental and ethical intelligence for conscious food choices (@hestia/sustainability). Food choices are one of the highest-impact areas of personal environmental behavior, and Hestia gives users the data to understand exactly where that impact falls — from carbon emissions per serving to labor conditions at the farm level.

• Carbon footprint: Carbon impact calculation for meals considering sourcing (local vs. imported), production method (conventional vs. organic), transport distance, processing, and cooking energy — expressed as kg CO₂-equivalent per serving.
• Food waste tracking: Waste categorization by type (vegetable peelings, spoiled produce, plate waste, trimming waste), waste reduction goal setting, composting guidance, and waste-reduction recipe suggestions that use typically discarded parts.
• Ethical sourcing: Evaluation of fair trade certification, organic certification, animal welfare standards (pasture-raised, free-range, cage-free designations and their actual meanings), and labor practice standards per ingredient and product.
• Seasonal and local sourcing: Seasonal availability data by region with farmer market integration, food mile calculation, and seasonal eating reminders.
• Composting guidance: Kitchen waste composting with carbon-to-nitrogen ratio management for effective composting — greens (nitrogen-rich: fruit scraps, coffee grounds, vegetable peelings) balanced against browns (carbon-rich: cardboard, dry leaves, straw). Note: eggshells are primarily calcium carbonate (a mineral amendment) and are not classified as greens or browns; they can be added to compost for calcium but do not contribute meaningfully to the C:N ratio.

11. Culinary Education#

Technique and Skill Development (@hestia/education)#

The education library covers culinary knowledge at every level of depth — from step-by-step knife skills for beginners to food science courses explaining the biochemistry of the Maillard reaction. The skill progression system tracks mastery levels and sequences techniques logically (you should understand sautéing before attempting advanced stir-frying), creating a structured path through culinary competency.

• Technique library: Detailed instruction for fundamental cooking methods — knife skills (mise en place, julienne, chiffonade, brunoise), heat management (searing, caramelization, Maillard reaction control), sauce making (roux, reduction, emulsification, liaison), bread baking fundamentals, and food preservation techniques (canning, fermentation, pickling, curing).

• Skill progression tracking: Mastery levels for techniques (beginner, developing, proficient, expert), practice session logging, and personalized learning paths that sequence techniques logically (learn sautéing before advanced stir-frying).

• Food science courses: The underlying chemistry and physics of cooking:

  • Maillard reaction: The non-enzymatic browning between amino acids and reducing sugars that produces hundreds of flavor compounds in seared meat, toasted bread, and roasted coffee
  • Emulsification: Dispersing one liquid in another immiscible liquid using an emulsifier — the principle behind mayonnaise, hollandaise, and vinaigrette
  • Gelation: Protein network formation (gelatin, pectin, starch gelatinization) that creates texture in custards, jams, and sauces
  • Fermentation: Microbial transformation of food by bacteria and yeast — sourdough, yogurt, kimchi, and cheese all created by controlled fermentation
  • Protein denaturation: How heat changes protein structure — the science of cooking eggs and meat perfectly

• Cuisine deep-dives: Essential techniques, core ingredients, characteristic flavor profiles, and signature dishes for major world cuisine traditions.

• Culinary certifications: Certification programs with structured curriculum (foundations, intermediate, advanced, cuisine specializations) with assessment and digital credential issuance.

• Interactive learning: Quizzes testing ingredient knowledge and food science, cooking challenges with judging criteria, and community feedback on submitted cooking results.

12. Professional Kitchen Tools#

Commercial and professional kitchen management capabilities (@hestia/professional). While the rest of Hestia targets home cooks, the professional library brings commercial-grade discipline to the platform — food cost accounting, HACCP compliance documentation, line-cooking workflow management, and the full catering event lifecycle from quotation to invoice.

• Menu costing: Food cost percentage calculation per dish (food cost ÷ selling price), plate cost tracking, and menu pricing optimization targeting specific food cost percentages and profit margins.
• Kitchen workflow optimization: Station assignments for line cooking (grill, sauté, fry, expo, prep), prep scheduling with quantity calculations from projected covers, and service timing optimization.
• Commercial inventory management: Par level setting (minimum stock quantity to trigger reorder), vendor management with contact information and lead times, purchase order generation, delivery tracking, and waste tracking for COGS (Cost of Goods Sold) accuracy.
• HACCP compliance: Hazard Analysis Critical Control Points monitoring — the FDA and USDA-mandated food safety management system — with critical control point logging (internal temperatures, holding temperatures, sanitation schedules) and audit-ready documentation.
• Catering and events: Event quotation with portion calculations, menu customization with dietary accommodation, staffing requirements, equipment rental lists, and event timeline planning.
• Recipe development: Professional recipe development workflow with version control, test batch tracking, sensory evaluation scoring, nutritional analysis, and scaling to production quantities.

13. Social Cooking#

Social features connecting cooks and building culinary communities (@hestia/social). The social layer turns cooking from a solitary activity into a connected one — sharing recipes with proper attribution, joining live cook- along events, competing in community challenges, and building family cookbooks together.

• Recipe sharing: Recipe publishing with privacy controls (public, friends-only, private), proper attribution when adapting others' recipes, and collaborative editing permissions.
• Cook profiles: Following relationships, activity feeds showing recent cooking activity, cooking statistics (recipes tried, cuisines explored, techniques mastered), and public recipe collections.
• Ratings and reviews: Recipe ratings (1–5 stars) with detailed written reviews, photo submissions of the cooked result, and "helpful" voting on reviews to surface the most useful feedback.
• Cook-alongs: Scheduled live cooking events where the host and participants cook the same recipe simultaneously — with synchronized timers, a chat stream, and the host's live video.
• Family cookbook: Shared family digital cookbooks with contribution management, comment threads on individual recipes, and integration with professional printing services.
• Community challenges: Cooking challenges with defined themes (e.g., "cook a dish from a cuisine you've never tried"), entry photo submission, community voting, and prizes or recognition for winners.

14. AI and Machine Learning Intelligence#

AI-powered culinary intelligence across all platform capabilities (@hestia/ai-ml). The AI/ML library is not a thin wrapper around a general LLM — it builds on the domain knowledge in every other library. Recipe generation is constrained by real ingredient data, flavor pairing recommendations are grounded in chemical compound analysis, and image recognition is trained on culinary vocabulary, not general object categories.

• Recipe generation: Novel recipe creation using LLMs constrained by available ingredients, dietary requirements, cuisine style, and desired cooking technique — generating workable recipes grounded in culinary knowledge rather than hallucinated nonsense.
• Flavor pairing AI: ML models trained on flavor compound data, traditional cuisine pairings, and user taste feedback for discovering non-obvious ingredient combinations — finding that coffee enhances chocolate not just by convention but because both are rich in pyrazines.
• Image recognition: Ingredient identification from photographs (recognizing a kabocha squash vs. butternut squash), dish identification from plated food photos with portion size estimation for nutritional logging without manual input.
• Personalized recommendations: Recipe and meal recommendations using collaborative filtering (what people with similar taste profiles enjoy) and content-based filtering (recipes similar to ones you've enjoyed) — improving with every rated recipe.
• NLP cooking assistant: Natural language cooking queries ("what can I make with these ingredients?", "what's the difference between braising and stewing?", "why did my hollandaise break?") and conversational cooking assistance during sessions.
• Predictive analytics: Grocery need forecasting (predicting what will be needed before it runs out), cooking trend identification (surfacing emerging food trends relevant to the user), and batch cooking schedule optimization.

15. Planned SOTA Enhancements#

The following capabilities are listed in TODOS.md phase 30.22 and represent the next expansion of Hestia's capabilities. They are planned but not yet implemented. Each section identifies a specific technology or data source that would unlock a new category of culinary intelligence.

Social Media Recipe Intelligence (planned)#

Short-form cooking videos on TikTok, Instagram Reels, and YouTube Shorts contain enormous recipe knowledge, but in a format that cannot be searched, scaled, or preserved. The goal here is to extract structured recipe data from these videos and bring them into the Hestia recipe model before they disappear.

• TikTok, Instagram Reels, YouTube Shorts recipe import: Parse and extract structured recipes from social media short-form cooking videos — using video transcription and visual AI to reconstruct ingredient lists and steps from unstructured video content.
• Viral recipe tracking: Identify trending recipes across social platforms and make them available for import before they disappear or become hard to find.
• In-app cooking video creation: TikTok-style cooking video creation tools — step markers that appear as on-screen overlays, recipe card integration, and one-tap social sharing.

Matter Protocol and Unified Smart Home (planned)#

The current smart kitchen integration requires a separate adapter per brand, creating a fragmented experience. Matter is the new unified connectivity standard (backed by Apple, Google, Amazon, and Samsung) that would let a single integration control any certified device regardless of brand.

• Matter 1.5 protocol support: Matter is the new unified smart home connectivity standard backed by Apple, Google, Amazon, and Samsung — implementing it enables Hestia to control any Matter-certified kitchen device regardless of brand.
• Cross-ecosystem compatibility: One interface for smart kitchen devices from Apple HomeKit, Google Home, Amazon Alexa, and Samsung SmartThings ecosystems — ending the fragmentation that currently requires separate apps per brand.
• Real-time energy tracking: Energy consumption tracking per cooking session — understanding the energy cost of different cooking methods (induction vs. gas vs. conventional oven vs. air fryer).
• Smart camera oven monitoring: Camera integration for supported smart ovens — enabling visual doneness checking from the phone without opening the oven door.

Advanced Wearable and Biometric Integration (planned)#

Continuous glucose monitors and fitness wearables can reveal how a specific meal affects a specific person — not population averages, but individual glycemic response. This enables a level of nutritional personalization that is impossible with general nutrition databases alone.

• Continuous glucose monitor (CGM) integration: Connect to CGM devices (Dexcom, Abbott, Signos, Veri) to see how specific meals affect blood glucose — enabling glycemic response personalization where the same meal affects different individuals very differently.
• Meal-to-glucose-spike correlation: Track which meals cause glucose spikes in the individual user — generating personalized glycemic response predictions for planned meals.
• HRV-based stress eating detection: Identify patterns where low HRV (high stress) correlates with food choice changes, enabling more compassionate and effective behavior coaching.
• Activity-aware meal suggestions: Use wearable activity data from Apple Watch, Garmin, or Fitbit to adjust caloric targets and macronutrient recommendations on high-activity vs. rest days.

Smart Refrigerator Camera AI (planned)#

• Samsung Family Hub / LG InstaView camera integration: Use internal fridge cameras to provide real-time inventory updates without manual scanning.
• Automatic inventory updates: AI-powered recognition of fridge contents from camera images — automatically updating the pantry inventory when items are added or removed.
• Produce freshness assessment: Visual assessment of produce freshness from fridge camera images — predicting remaining shelf life and surfacing recipes to use items before they spoil.
• "What's in my fridge" recipes: Generate meal suggestions from the current fridge inventory as identified by camera, reducing food waste and eliminating the "nothing to eat" feeling.

Microbiome-Aware Nutrition (planned)#

Your gut microbiome composition is as individual as a fingerprint, and it determines which foods are most beneficial for you specifically — not just in theory but in measurable terms of energy, immunity, and mood. ZOE and Viome consumer tests are making this data accessible.

• ZOE/Viome gut health integration: Import personalized gut microbiome test results (which bacterial species are present and in what proportions) and use them to personalize meal recommendations — your gut microbiome composition determines which foods are most beneficial for you specifically.
• Microbiome-friendly meal scoring: Score meals based on their likely impact on the user's specific gut microbiome composition — promoting prebiotic-rich and probiotic-supportive meals.
• Gut-brain axis optimization: Plan meals that support the gut-brain connection — fermented foods, prebiotic fibers, and polyphenol-rich ingredients associated with improved mood and cognitive function.

Restaurant and Dining Out Integration (planned)#

For people with severe food allergies, eating out is genuinely dangerous. A multilingual allergen card and a crowd-sourced database of restaurant safety practices could meaningfully reduce that risk.

• Restaurant allergen database: Spokin-style comprehensive restaurant allergen database for safe dining out with food allergies.
• Dining out allergy cards: Generate multilingual allergy cards (40+ languages) for communicating dietary restrictions to restaurant staff when traveling internationally.
• Menu allergen parsing: Automatically parse restaurant menus to flag dishes that may contain specific allergens.
• Allergy-friendly restaurant discovery: Location-based discovery of restaurants known to accommodate specific dietary restrictions, with crowd-sourced safety ratings.