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AI, QUALITY & DELIVERY

Hire AI developers in India

Engineers who build real products on top of existing AI models.

Add AI developers who turn a promising prototype into something your business can actually run — chatbots, AI agents, retrieval assistants and LLM integrations, built with evaluation and a human in the loop. We build on existing models; we do not train foundation models from scratch.

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WHO THIS SUITS

The right fit for your team.

← All roles & technologies
  • Teams with an AI prototype that now needs to be integrated into a real workflow
  • Product owners adding an assistant, chatbot or agent to an existing application
  • Companies with internal knowledge they want to make searchable and useful

PROBLEMS WE HELP SOLVE

The situations that bring teams to us.

  • A demo impressed everyone but there is no path from prototype to production
  • An assistant needs to answer from your own content, accurately and with sources
  • AI output needs review, guardrails and monitoring before it can be trusted
  • LLM features need to connect to real systems, data and approvals — not just chat

WHAT THEY CAN HELP YOU DELIVER

Concrete work, not job titles.

  • Build a retrieval-augmented (RAG) knowledge assistant over your documents, with citations
  • Integrate an LLM into an existing product with prompt, context and cost controls
  • Build an AI agent or workflow that takes actions, with human review at the decisions that matter
  • Add evaluation, logging and monitoring so quality and cost are measured in production

TECHNICAL CAPABILITIES

Matched to your stack.

OpenAI / Anthropic / open modelsRAG & vector searchLangChain / LlamaIndexPython / TypeScriptEmbeddingsWorkflow orchestrationEvaluation & monitoringFastAPI / Node.js
  • LLM integration with hosted and open models; prompt and context design
  • Retrieval-augmented generation, embeddings and vector search
  • Agent and workflow orchestration with human-in-the-loop review steps
  • Evaluation, guardrails, logging and cost/latency monitoring
  • Backends in Python or Node.js that connect AI to real systems and data

HOW COLLABORATION WORKS

Part of your team, not a black box.

  1. 01 /

    Shared scope

    We agree the use case, the data involved and what 'good enough to ship' means before building.

  2. 02 /

    Human in the loop

    For anything consequential we design review and fallback steps rather than full autonomy.

  3. 03 /

    Overlap hours

    Overlap for reviews and iteration on prompts and behaviour is agreed per engagement.

  4. 04 /

    Measured quality

    We instrument evaluation, accuracy and cost so decisions rest on evidence, not demos.

WAYS TO ENGAGE

Choose the model
that fits the work.

From one specialist to a dedicated team or a managed delivery. Availability, communication and commercial terms are agreed in writing before anyone starts.

Compare engagement models in detail →

COMMON QUESTIONS

Clear answers before you commit.

Do you train your own AI models?

No. We build applications on top of existing hosted and open models — integration, retrieval, agents, evaluation and production engineering. We do not carry out foundation-model research or training, and we will say so plainly rather than imply otherwise.

How do you keep AI output reliable?

We design for it: grounding answers in your data, adding validation and human review for anything that matters, and instrumenting evaluation and monitoring so quality and cost are measured, not assumed.

Can you integrate AI into our existing product?

Yes — that is most of the work. We connect models to your data, systems and approval steps and ship behind your existing auth and infrastructure.

Our own products use AI — is this real experience?

Yes. ARSTEG builds and operates AI-powered products of its own, including an AI GST-compliance platform and an AI outbound-sales platform, both designed around human approval before anything consequential happens.

DISCUSS YOUR REQUIREMENTS

Tell us the skills
or the work.

A developer with a specific skill, a team to extend your capacity, or a project to deliver. Tell us where you are and where you want to go.

  1. Share the role, skills or project and your constraints.
  2. We discuss the fit, availability and open questions.
  3. Agree an engagement model, overlap and next step.

Discuss your project

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