luminovainfotech

AI

Generative AI

Build, evaluate, and operate GenAI solutions in production

We design and ship generative AI applications that solve real business problems — not demos. From retrieval-augmented systems to document automation to internal copilots, we cover the full path from prototype to a governed production system.

What we deliver

Generative AI capabilities, end to end

Retrieval-Augmented Generation (RAG)

Grounded GenAI applications that combine LLMs with your data — built with the retrieval, ranking, and observability that determine whether they work in production.

  • Document ingestion and chunking pipelines for messy enterprise data
  • Hybrid search with dense vectors and BM25 / keyword retrieval
  • Reranking, citation, and answer-grounding patterns
  • Latency and cost tuning, caching, and structured outputs

Internal copilots and assistants

Domain-tuned assistants for support, sales, ops, and back-office teams. We design the interface, the agent loop, and the integrations that make them useful day one.

  • Conversational interfaces in Slack, Teams, web, and email
  • Tool-use integrations with your CRM, ticketing, and data platforms
  • Role-based access controls and audit logging
  • Feedback loops that improve the assistant over time

Document automation

Extract, classify, summarize, and act on unstructured documents at scale — contracts, claims, invoices, reports.

  • OCR, layout understanding, and multimodal extraction
  • Schema-validated structured output via constrained decoding
  • Human-in-the-loop review queues for low-confidence cases
  • Integration with downstream systems of record

Evaluation, safety, and guardrails

We build the evals before the model — and the guardrails before the launch. Production GenAI without these is theater.

  • Task-specific eval suites and golden datasets
  • LLM-as-judge and human evaluation workflows
  • Prompt injection, jailbreak, and PII red-teaming
  • Runtime guardrails, content filtering, and policy enforcement

How we work with you

Engagement shapes

Three typical ways we engage on generative ai — adapted to your scope, timeline, and team.

4–6 weeks

GenAI Prototype

Working prototype for a single use case, with eval suite and deployment plan.

8–16 weeks

Production GenAI Build

Full production system with retrieval, evals, guardrails, monitoring, and handover.

Ongoing

GenAI Managed Service

We operate the system: monitoring, drift detection, prompt and retrieval iteration, model updates.

Tools & technologies

Built on what your teams already know

We work with industry-standard tooling and open standards — no proprietary lock-in.

Model providers
Anthropic ClaudeOpenAIGoogle GeminiMistralCohereopen-weight models on AWS / Azure / GCP
Frameworks
LangChainLlamaIndexDSPyAnthropic SDKOpenAI SDK
Vector & search
PineconeWeaviatepgvectorElasticsearchOpenSearch
Evaluation
BraintrustLangSmithPromptfooRagascustom eval harnesses

Let's talk

Tell us what you're building.

Share the shape of your initiative and we'll respond within one business day with a tailored point of view — and the names of the senior people who would lead the work.

Opens in your email app — review and click Send.