Build production-grade applications with Supabase, database, auth, real-time, storage, and Edge Functions with AI integration. Our Bengaluru team delivers full-stack Supabase implementations with a focus on serverless AI features, pgvector semantic search, and LLM-powered application backends.
Proof-First Delivery
What We Offer
Each module is designed as a production block with integration boundaries, governance hooks, and measurable outcomes.
Full-Stack Supabase Application Development End-to-end application development on Supabase, PostgreSQL database design, Row Level Security, real-time subscriptions, auth flows, and storage configuration. We build applications that leverage Supabase's full feature set instead of treating it as just a database. Edge Functions for AI Features Build AI-powered features using Supabase Edge Functions, LLM API integration with streaming, semantic search endpoints, RAG pipelines, AI chatbot backends, and content generation workflows. We handle the architecture so your AI features are fast, reliable, and cost-efficient. pgvector Semantic Search Implement vector search directly in your Supabase PostgreSQL database using pgvector. Semantic product search, document retrieval, recommendation engines, and similarity matching, all within your existing database without adding new infrastructure. Migration to Supabase Migrate from Firebase, custom backend APIs, or other BaaS platforms to Supabase. We handle data migration, auth system transition, API endpoint mapping, and real-time subscription conversion with minimal downtime and no data loss.
How We Work: From Discovery to Production Every Supabase engagement starts with a discovery session where we audit your existing data model, authentication requirements, and AI feature goals. We map out which Supabase capabilities address each requirement directly, and identify where custom Edge Functions or external services are needed. This scoping phase, typically two to three days, produces a written architecture document and implementation plan before any code is written. Database Schema and Security Design We design your PostgreSQL schema with AI features in mind from the start: vector columns for embeddings, JSONB columns for LLM response metadata, audit tables for AI interaction logging, and indexes tuned for the query patterns your application will actually run. Row Level Security policies are written alongside the schema, not added as an afterthought, so every table has its access rules defined before the first line of application code. Edge Function Development and Testing Our Edge Function development follows a test-first approach. Each function is developed locally using the Supabase CLI, tested against a local Supabase instance with seeded data, and reviewed for performance before deployment. We instrument functions with structured logging from day one, so production issues are diagnosable without adding observability retroactively. Functions are version-controlled with the application codebase, not managed separately. AI Integration and Prompt Engineering We build AI integrations with production reliability in mind: retry logic for rate-limited LLM API calls, fallback models when the primary model is unavailable, response validation to catch hallucinations or malformed outputs, and prompt versioning so you can compare outputs across prompt iterations. Prompt templates are stored in your database, not hardcoded in function source, which lets you update AI behavior without redeploying functions.
What You Receive at Project Completion Every Supabase project we deliver includes a production-ready application deployed to your own Supabase organization, full database schema with migrations tracked in version control, all Edge Function source code with tests, a local development setup guide so your team can run the full stack locally, and a runbook covering common operational tasks (database backups, scaling storage, rotating API keys, monitoring Edge Function performance). For AI-integrated projects, deliverables additionally include: a prompt library document capturing all system prompts and their rationale, an embedding strategy document explaining which text fields are embedded, which model is used, and how re-embedding should be triggered after model upgrades, and a cost monitoring dashboard showing LLM API spend broken down by feature and endpoint.
Who Works on Your Project A typical Supabase engagement at Boolean and Beyond involves a backend engineer with Supabase and PostgreSQL expertise, a full-stack TypeScript engineer for Edge Functions and any frontend integration work, and an AI/ML engineer for LLM integration design, prompt engineering, and embedding pipeline architecture. For larger engagements or those requiring mobile clients, we add a React Native or Flutter engineer as needed. Every project has a dedicated technical lead who is your primary contact throughout. The technical lead runs the weekly status call, reviews all pull requests before they are merged, and makes the final call on architecture decisions. You communicate directly with the people building the product, not through a project manager intermediary. Our Bengaluru team operates in IST, which gives us workday overlap with both European and Southeast Asian clients and a six-hour window with US East Coast business hours. For US West Coast clients, we structure async handoffs so that you receive progress updates at the start of your workday and can provide feedback that our team acts on overnight.
We combine deep Supabase expertise with production AI engineering experience. Most Supabase agencies build CRUD apps. We build intelligent applications, with semantic search, AI-generated content, real-time AI features, and serverless inference pipelines running on Supabase's infrastructure.
Delivery Proof
Selected engagements that show architecture depth, execution quality, and measurable business impact.
Delivery Advantages
Full-Stack Supabase Application Development End-to-end application development on Supabase, PostgreSQL database design, Row Level Security, real-time subscriptions, auth flows, and storage configuration. We build applications that leverage Supabase's full feature set instead of treating it as just a database. Edge Functions for AI Features Build AI-powered features using Supabase Edge Functions, LLM API integration with streaming, semantic search endpoints, RAG pipelines, AI chatbot backends, and content generation workflows. We handle the architecture so your AI features are fast, reliable, and cost-efficient. pgvector Semantic Search Implement vector search directly in your Supabase PostgreSQL database using pgvector. Semantic product search, document retrieval, recommendation engines, and similarity matching, all within your existing database without adding new infrastructure. Migration to Supabase Migrate from Firebase, custom backend APIs, or other BaaS platforms to Supabase. We handle data migration, auth system transition, API endpoint mapping, and real-time subscription conversion with minimal downtime and no data loss.
How We Work: From Discovery to Production Every Supabase engagement starts with a discovery session where we audit your existing data model, authentication requirements, and AI feature goals. We map out which Supabase capabilities address each requirement directly, and identify where custom Edge Functions or external services are needed. This scoping phase, typically two to three days, produces a written architecture document and implementation plan before any code is written. Database Schema and Security Design We design your PostgreSQL schema with AI features in mind from the start: vector columns for embeddings, JSONB columns for LLM response metadata, audit tables for AI interaction logging, and indexes tuned for the query patterns your application will actually run. Row Level Security policies are written alongside the schema, not added as an afterthought, so every table has its access rules defined before the first line of application code. Edge Function Development and Testing Our Edge Function development follows a test-first approach. Each function is developed locally using the Supabase CLI, tested against a local Supabase instance with seeded data, and reviewed for performance before deployment. We instrument functions with structured logging from day one, so production issues are diagnosable without adding observability retroactively. Functions are version-controlled with the application codebase, not managed separately. AI Integration and Prompt Engineering We build AI integrations with production reliability in mind: retry logic for rate-limited LLM API calls, fallback models when the primary model is unavailable, response validation to catch hallucinations or malformed outputs, and prompt versioning so you can compare outputs across prompt iterations. Prompt templates are stored in your database, not hardcoded in function source, which lets you update AI behavior without redeploying functions.
What You Receive at Project Completion Every Supabase project we deliver includes a production-ready application deployed to your own Supabase organization, full database schema with migrations tracked in version control, all Edge Function source code with tests, a local development setup guide so your team can run the full stack locally, and a runbook covering common operational tasks (database backups, scaling storage, rotating API keys, monitoring Edge Function performance). For AI-integrated projects, deliverables additionally include: a prompt library document capturing all system prompts and their rationale, an embedding strategy document explaining which text fields are embedded, which model is used, and how re-embedding should be triggered after model upgrades, and a cost monitoring dashboard showing LLM API spend broken down by feature and endpoint.
Who Works on Your Project A typical Supabase engagement at Boolean and Beyond involves a backend engineer with Supabase and PostgreSQL expertise, a full-stack TypeScript engineer for Edge Functions and any frontend integration work, and an AI/ML engineer for LLM integration design, prompt engineering, and embedding pipeline architecture. For larger engagements or those requiring mobile clients, we add a React Native or Flutter engineer as needed. Every project has a dedicated technical lead who is your primary contact throughout. The technical lead runs the weekly status call, reviews all pull requests before they are merged, and makes the final call on architecture decisions. You communicate directly with the people building the product, not through a project manager intermediary. Our Bengaluru team operates in IST, which gives us workday overlap with both European and Southeast Asian clients and a six-hour window with US East Coast business hours. For US West Coast clients, we structure async handoffs so that you receive progress updates at the start of your workday and can provide feedback that our team acts on overnight.
FAQ
Ready to build your AI-powered application on Supabase? Talk to our Bengaluru team about your project.