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AI Solutions that actually ship.

We build production-ready AI — RAG systems, document extraction, chat agents, and computer vision. No research projects. No demos that stay demos.

Our approach

We learned AI by using it ourselves first — automating our own workflows, building internal tools, breaking things.

Every solution we ship has been stress-tested by engineers who actually use AI daily.

What we build

Six core AI capabilities.

📄

Document AI

Extract structured data from PDFs, invoices, contracts, and handwritten forms.

InvoicesContractsMedical forms
99.4% extraction accuracy
🔎

RAG Systems

Retrieval-augmented generation for enterprise search, support bots, and knowledge bases.

Knowledge baseSupport botLegal search
73% ticket deflection
💬

Chat & Agents

Conversational AI that completes tasks — book appointments, process returns, trigger workflows.

Customer supportSales agentBooking
RoleplayPro.in →
👁️

Computer Vision

Quality inspection, defect detection, and visual analysis for manufacturing and healthcare.

Defect detectionQA automationEdge AI
4x faster QA, -62% scrap
🎛️

LLM Integration

Add intelligence to your product. Claude, GPT-4, Gemini, or open-source — with guardrails.

Claude / GPT-4Llama / MistralGuardrails
API-first or self-hosted
⚙️

MLOps & Infra

Model deployment, monitoring, versioning, and scaling. AI that works on day 365.

Model monitoringA/B testingAuto-scaling
AWS / GCP · Docker
How an AI project works

From idea to production in four stages.

WEEK 1-2

Discovery

Map data, define metrics, identify approach. No code yet.

WEEK 3-5

Prototype

Working POC on your real data. Test edge cases.

WEEK 6-12

Production

Harden pipeline, integrate systems, set up monitoring.

ONGOING

Iterate

Monitor accuracy, retrain models, optimize costs.

Got an AI problem worth
solving?

Tell us about it. First call is free, and we'll give you an honest assessment.