Add AI to your product. Ship in days.

From LLM integration to on-device inference: production AI features built by a hackathon-winning team with deep expertise across the AI stack.

Top 6 at GitHub HQ Hackathon (Meta & Cerebral Valley)

AI demos are easy. Production AI is hard.

Most AI features stall between prototype and production. We bridge that gap by shipping reliable, scalable AI that works in the real world.

AI capabilities

LLM Integration

Integrate OpenAI, Claude, and open-source models into your product. Chat interfaces, content generation, and intelligent automation.

AI Agents & Workflows

Autonomous agents that reason, plan, and execute. Tool-calling, MCP protocol integration, and complex multi-step workflows.

RAG Pipelines

Retrieval-augmented generation over your data. Vector search, document processing, and grounded AI responses.

On-Device AI

Edge inference with ExecuTorch and TinyLlama. Privacy-first AI that runs entirely on the user's device, with zero cloud dependency.

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Years of experience

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Projects delivered

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Response time

How it works

01

Discovery

We map your AI use case, data sources, and success criteria. You get a clear plan within 48 hours.

02

Architecture

Design the AI pipeline: model selection, data flow, evaluation metrics, and integration points.

03

Build

Rapid prototyping and iteration. Working demos within days, production deployment within weeks.

04

Launch

Deploy with monitoring, evaluation, and guardrails. Ongoing optimization and model updates.

Ready to add AI to your product?

Tell us about your use case. We will show you what is possible and how fast we can deliver.

Frequently asked questions

Can you add AI to our existing product?

Absolutely. Most of our AI work involves integrating intelligent features into existing applications: chat interfaces, content generation, smart search, and automated workflows. We work with your existing codebase and infrastructure.

Do you build production AI or just prototypes?

Production AI, always. Our hackathon-winning background means we prototype fast, but every feature we ship is built with proper error handling, evaluation, monitoring, and scale in mind. No demo-ware.

What AI models and frameworks do you work with?

We work with OpenAI, Anthropic Claude, open-source models (Llama, Mistral), LangChain, and edge AI frameworks like ExecuTorch. We choose the right tool for each use case: cost, latency, and privacy all factor in.

How do you handle data privacy and security?

We design AI systems with privacy by default. Options include on-device inference, private model deployments, and strict data handling policies. We can build fully offline AI solutions when needed.

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