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Deepak Suhag
🤖 GenAI Engineering

FAQs: GenAI Engineering Services in Thillai Nagar

Anyone can wire up an API call. Shipping a GenAI feature that's reliable, cost-aware and safe under real user load for a Thillai Nagar business is a different job — that's what I do.

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10+
Years experience
3–10×
Avg ROAS
Global
Markets served
<24 hrs
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FAQ

Everything you need to know

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01Which LLM providers do you work with for Thillai Nagar clients?

OpenAI, Anthropic (Claude), and open-source models via providers like Together or self-hosted where it makes sense.

02Can you build RAG systems for Thillai Nagar businesses?

Yes — retrieval-augmented generation with vector databases is a core part of the work.

03How do you handle hallucination risk?

Grounded retrieval, structured outputs, automated evals, and human-review checkpoints for anything customer-facing.

04Do you build the whole product or just the AI layer?

Either — I can own the full feature end-to-end, or plug into your existing Thillai Nagar engineering team.

05What does a GenAI engineering engagement cost in Thillai Nagar?

Cost depends on whether you need a single feature (prompt design plus RAG, for example) or a full evaluation and monitoring layer around an existing feature. Share what your Thillai Nagar team is trying to ship for a specific quote.

06How is this different from hiring a general software agency for AI work in Thillai Nagar?

A general agency in Thillai Nagar can usually wire up an API call but rarely builds the evaluation harness, guardrails and cost-aware routing needed to keep quality from silently regressing after launch — that production-hardening layer is the core of this work.

07How long until a GenAI feature is production-ready for our Thillai Nagar product?

A scoped feature with RAG and basic evals typically takes 3-6 weeks from architecture to launch, depending on how much of your Thillai Nagar business's data needs to be ingested and indexed first.

08Is this a good fit if we just want to try an AI chatbot experiment in Thillai Nagar?

For a quick, low-stakes internal experiment, a lighter no-code tool is often the faster and cheaper starting point. This is built for Thillai Nagar teams shipping an AI feature to real customers, where reliability and cost control actually matter.

09What happens in the first week for a Thillai Nagar engagement?

The first week defines the exact use case, likely failure modes, and success metrics for your Thillai Nagar product before a single prompt gets written — so the evaluation criteria exist before the build does.

🤖 GenAI Engineering · Thillai Nagar

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