Full-Stack AI Engineering Studio

Turning Bytes
into Brilliant
Products.

From idea to deployment, we engineer scalable AI-driven products that bring your startup vision to life. 20+ products shipped.

20+
products built
5+
AI stacks shipped
4
core platforms
SCROLL
Full-Stack EngineeringRAG PipelinesReact NativeMulti-Agent SystemsMVP SprintVoice AIVector SearchNext.js + SupabaseLangChain / LangGraphComfyUIn8n AutomationLLM IntegrationFull-Stack EngineeringRAG PipelinesReact NativeMulti-Agent SystemsMVP SprintVoice AIVector SearchNext.js + SupabaseLangChain / LangGraphComfyUIn8n AutomationLLM Integration

How We Build

From your idea to a live product.

We start with discovery, understanding your business before a single line of code is written. Then we architect, build, and deploy with full-stack precision across web, mobile, AI, and cloud.

Three environments from day one
Continuous communication throughout the build
We say no when features don't belong
Full handoff with docs and knowledge transfer
DiscoveryScope & StrategyArchitectureSystem DesignAI PlanningLLMs & AgentsWeb AppNext.js + SupabaseMobile AppReact Native + ExpoAI IntegrationAgents, RAG, VectorsCloud & DevOpsAWS / Vercel / CI/CD

← scroll to explore diagram →

Agentic AI

We build agents that think, decide, and act.

Agentic AI goes beyond chatbots. We design multi-step reasoning systems that use tools, query knowledge bases, delegate subtasks, and operate autonomously at production scale.

OrchestratorResearch AgentCode AgentData AgentOutput Agent

← scroll to explore diagram →

Orchestrator + Specialist Agents

Multi-Agent Systems

We build systems where a central orchestrator agent breaks down complex tasks and delegates to specialist sub-agents — each with its own tools, memory, and context. Built with LangGraph and Claude Agent SDK.

AI Engineering

MongoDB VectorPineconepgvector

We build RAG systems that actually work in production.

Retrieval-Augmented Generation lets your product answer questions grounded in your own data. We've built RAG pipelines on MongoDB Atlas Vector Search, Pinecone, and Supabase pgvector — handling ingestion, chunking, embedding, retrieval and LLM orchestration end to end.

RAG Architecture

INGESTION PIPELINEQUERY PIPELINESource DataPDFs · Docs · WebChunkerText splittingEmbeddingsOpenAI · LocalVector StorePinecone · MongoDBpgvectorUser QueryNatural languageQuery EmbedSame modelSemantic SearchCosine similarityTop-K ContextRelevant chunksLLMGPT-4 · ClaudeGeminiResponseGrounded answer

← scroll to explore diagram →

Managed

MongoDB Atlas Vector Search

Fully managed vector search alongside your operational data. Store embeddings with your documents — no separate infra needed. We use it for semantic search in production apps.

Dedicated

Pinecone

Purpose-built vector database for high-scale semantic search. Sub-millisecond query latency. We use Pinecone when you need dedicated vector infra at scale with filtering.

Integrated

Supabase pgvector

PostgreSQL-native vector extension — perfect for our Next.js + Supabase MVP stack. Full vector search with the simplicity of SQL. Embeddings live right next to your user data.

AI Capabilities

Full-spectrum AI engineering.

We don't just integrate AI. We understand the architecture, the science, and the tooling — from embeddings to multi-agent orchestration. Built through real R&D, shipped in production products.

LLMs & Models
OpenAI GPT-4oClaude (Anthropic)GeminiAWS BedrockVertex AILlama IndexPrompt EngineeringMulti-Agent Systems
Voice AI
Retell AIElevenLabsVapiVoice AgentsReal-time TTSConversational AIIVR Automation
Image & Video Gen
ComfyUIRunPodStable DiffusionTripo AI (3D)Image PipelinesVideo GenerationMLOPS
Automation & Agents
n8n WorkflowsLangChainLangGraphMCP ServerClaude Agent DevAgentic AIContent Automation
Vector & Search
RAG PipelinesMongoDB VectorPineconepgvectorEmbeddingsSemantic SearchKnowledge Graphs
Infrastructure & Ops
AWS BedrockCI/CD PipelinesCost CachingEdge DeploymentToken OptimizationRate LimitingMonitoring & Evals

Automation & Voice AI

Agents that work while you sleep.

From n8n workflow automation to real-time voice agents powered by Retell, ElevenLabs and Vapi. We build AI systems that operate autonomously and handle real workloads.

n8n
Workflow Automation

We build complex multi-step automations with n8n — connecting your CRM, APIs, databases and AI models into seamless workflows that run without you.

Retell AI
Voice Agents

Intelligent voice agents that can handle inbound calls, qualify leads, and conduct conversations at scale. Powered by real-time LLMs.

ElevenLabs
Voice Synthesis

Ultra-realistic text-to-speech for your product. Custom voice cloning, multilingual, low-latency — integrated into web apps, mobile, and agents.

Vapi
Voice API Platform

Production voice AI infrastructure. We use Vapi to build real-time conversational agents with sub-300ms latency on top of OpenAI, Claude, and Gemini.

From Idea to Launch

How we take your idea and ship it.

A clear, repeatable process built on discipline. From requirements to deployment to post-launch AI tooling — every step designed to protect your time and budget.

01💡

Idea & Requirements

We turn your idea into a clear product brief. What problem does it solve? Who uses it? What does success look like? We ask the hard questions upfront so nothing gets wasted downstream.

Discovery CallUser StoriesScope Doc
02⚙️

Platform & Stack

Web app or mobile? Next.js + Supabase for web MVPs. React Native + Expo for cross-platform mobile. AWS for enterprise. We pick the stack that fits your timeline and budget, not ours.

Tech SelectionArchitectureCost Estimate
03🎯

Feature Prioritization

We ruthlessly cut scope to what's essential. MoSCoW method, user flow mapping, sprint planning. You get a product people use — not a bloated spec that never ships.

MoSCoWSprint PlanMVP Definition
04🔨

Build & Iterate

Agile sprints, weekly demos, continuous feedback. Three environments from day one. You see real progress every week — not a big reveal at the end.

Agile SprintsWeekly Demos3 Environments
05🚀

Deploy with CI/CD

Production-grade deployment with automated CI/CD pipelines. GitHub Actions, Vercel, or AWS Amplify. Automated tests run on every push. Zero-surprise releases.

GitHub ActionsVercel / AWSZero-downtime
06🤖

AI & Cost Optimization

We integrate agentic AI tools for marketing, support, and ops. We also apply caching strategies, token optimization, and edge functions to minimize your monthly running costs from day one.

Agentic ToolsResponse CachingCost Modeling

How We Collaborate

Your project deserves more than code.

We treat your startup like it's our own. That means honesty, discipline, and real ownership of outcomes.

01

Scope before we code

Discovery call first. We learn your business, define what to build and more importantly what not to. No assumptions, no wasted sprints.

02

We say no when needed

Not every feature belongs in an MVP. We protect your timeline and budget by keeping scope focused and the product tight.

03

Three environments, always

Dev, Staging, Production. Non-negotiable. Every project ships with CI/CD pipelines and zero-surprise deploys.

04

Speed through discipline

We move fast because our systems are tight, not because we cut corners. Quality code, tested, documented, handed over.

Our Philosophy

We know what it takes to build something real.

Founded at 25, we've been in the trenches. Every dollar you invest in your product means something to us, because we know what it's like to put everything into an idea.

We're upfront: we'll tell you exactly what to build and what you don't need. Not every feature belongs in an MVP. We help you prioritize ruthlessly, move fast, and get to market.

0+
Products Built
Web, mobile and AI
0+
AI Stacks Shipped
RAG, agents, voice
0
Environments
Dev, Staging, Prod
0%
Upfront Honesty
We say no when right

Ready to build something remarkable?

Let's turn your idea into a product people actually use. We'll be upfront about exactly what it takes — and what it doesn't.