Generative AI Development Company

Generative AI That Ships to Production

Most generative AI work dies at the demo stage: no grounding, no evaluation, no guardrails. GTS Infosoft builds the version that survives production — retrieval-augmented generation, fine-tuning and tool-using agents, paired with the evals and safety controls that keep output accurate, on-brand and within budget.

Founded in 2010 and ISO 9001:2015 certified, we've shipped 250+ apps across 16 years for clients in India, the USA and Australia. Our AI engineers work with OpenAI, Anthropic and open models — Python, vector databases, MLOps — and deliver generative features from around USD 20 an hour with AI-accelerated delivery and time-zone overlap.

Rated top developers on

ISO 9001:2015 Certified

What We Build With Generative AI

RAG over your data
Retrieval-augmented generation grounded in your documents and databases via vector search. Answers stay accurate, and citable.
Assistants and copilots
Domain-specific chat assistants and in-app copilots that draft, summarise and answer inside your product.
Content and document generation
Pipelines that generate, transform and pull structured content out of text, documents and images at scale.
Fine-tuned and custom models
Fine-tuning and prompt engineering across OpenAI and open models until output matches your tone, format and domain.

How We Make It Production-Ready

Evals and quality gates
Evaluation suites that track accuracy, hallucination and regressions. Quality gets measured, not assumed.
Guardrails and safety
Input and output guardrails, content moderation and grounding keep every generation safe, on-brand and on-policy.
Cost and latency control
Model routing, caching and prompt optimisation hold token spend and latency down as usage climbs.
Monitoring and iteration
Logging, tracing and feedback loops, so you can debug, refine prompts and retrain as real traffic arrives.

Why GTS Infosoft for Generative AI

Model-agnostic
OpenAI, Anthropic or open models — we pick per use case, weighing quality against cost and privacy.
Full-stack delivery
The AI lands inside real apps and back ends, not in a notebook nobody deploys. Features actually reach users.
Senior, ISO-certified team
ISO 9001:2015 process, experienced AI engineers from around USD 20 an hour, and working hours that overlap yours.
Data privacy first
Sensitive data can stay on self-hosted open models, handled under NDA with strict access controls.

The Generative AI Stack We Use

OpenAI APIAnthropic ClaudeLangChainPythonVector DBs (Pinecone/pgvector)Hugging FaceNode.jsAWS

Frequently Asked Questions

How much does generative AI development cost?

Depends on your data readiness, the model, and scope. We scope the use case first, then send a clear estimate — engineers run from around USD 20 an hour and the design itself keeps token and compute costs down.

What is RAG and do I need it?

Retrieval-augmented generation means the model answers from your own data, found via vector search, which cuts hallucination sharply. If you need accurate answers from your documents or database, RAG is usually where you start.

Which models do you work with?

We're model-agnostic — OpenAI, Anthropic Claude, open models — and choose per use case on quality, cost and privacy. For sensitive data, self-hosted open models are on the table.

How do you keep generative AI accurate and safe?

Grounding via RAG, evaluation suites, and input and output guardrails with content moderation, plus logging and monitoring. Quality and safety get measured continuously, not checked once.

Can you add generative AI to my existing product?

Yes. We wire generative features into your existing apps and back ends — retrieval, prompts, guardrails, evals — so the AI ships as a dependable part of the product.