AI & Automation

LLM apps, RAG pipelines, document automation, and AI agents integrated into your existing stack.

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Service overview

AI & Automation

We build production AI: RAG-backed knowledge assistants, document extraction pipelines, agentic workflows, and LLM-powered features inside your existing app. Anthropic Claude, OpenAI GPT, and open-weight models — whichever fits the eval and budget.

Real shipping, not demos. Every engagement includes evals, observability, prompt versioning, and a clear human-in-the-loop story. We've shipped AI features into Zoho CRM, Webflow sites, custom SaaS, and customer support workflows.

Production RAG + agentic workflows

Multi-step agents with retrieval, tool use, and human approval gates.

Production RAG + agentic workflows

Multi-step agents with retrieval, tool use, and human approval gates.

Document automation at scale

Invoice/contract extraction, KYC docs, support tickets — accuracy benchmarked weekly.

Document automation at scale

Invoice/contract extraction, KYC docs, support tickets — accuracy benchmarked weekly.

Evals + observability built in

LangSmith, Braintrust, or custom eval harness from sprint one.

Evals + observability built in

LangSmith, Braintrust, or custom eval harness from sprint one.

Zoho + Salesforce native

Drop AI into CRM workflows: summaries, next-best-action, deal scoring.

Zoho + Salesforce native

Drop AI into CRM workflows: summaries, next-best-action, deal scoring.

What's included

What’s included

Category

Details

What we ship

RAG knowledge bases on Pinecone / pgvector
Agents using Anthropic Claude + tools
Document extraction (PDFs, emails, forms)
Voice + chat assistants
Embedded AI in CRM workflows

Stack we use

Claude 4.x, GPT-4o/5, open-weight models
LangChain, LlamaIndex, custom orchestrators
Pinecone, pgvector, Weaviate
LangSmith, Braintrust for evals
Vercel AI SDK, Anthropic SDK

Typical engagement

Week 1-2: Use-case scoping + eval design
Week 3-6: Prototype + golden-set eval
Week 7-10: Production hardening + observability
Week 11-12: Launch + monitoring dashboards
Ongoing: Drift detection + tuning

Simple & Transparent

Our proven workflow

Download brochure

Step 1

Discovery & scoping

Step 2

Build & implementation

Step 3

QA, launch & support

Common questions

Frequently asked questions

Which models do you use?

We start with Claude or GPT for prototyping, then evaluate open-weight alternatives (Llama, Mistral) if cost or latency matters at production scale.

How do you handle accuracy?

Can AI features run on our infra?

What about hallucinations?

How quickly can we see results?