Generative AIDevelopment
LLM-powered content, search and knowledge experiences grounded in your data. Built on your data, integrated with your systems and governed for enterprise use.
Use Cases
Where Generative AI creates measurable operational ROI today.
Enterprise search (RAG)
Production-ready enterprise search (rag) engineered with strict latency, safety, and evaluation benchmarks.
Content generation
Production-ready content generation engineered with strict latency, safety, and evaluation benchmarks.
Document summarization
Production-ready document summarization engineered with strict latency, safety, and evaluation benchmarks.
Code assistants
Production-ready code assistants engineered with strict latency, safety, and evaluation benchmarks.
What We Deliver
Strategy & roadmap
Use-case discovery, ROI modelling and a phased generative ai delivery roadmap.
Data foundation
Secure ingestion pipelines, vector indices and metadata governance so models get clean context.
Build & integrate
Production model orchestration, custom agents and REST/gRPC APIs integrated with your core workflows.
Evaluation & safety
Comprehensive safety guardrails, hallucination testing and performance latency benchmarks.
MLOps / LLMOps
Automated deployment, token spend monitoring with Trasys AI, and continuous regression suites.
Enablement
Technical documentation, architecture blueprints and team training so your squad owns the system.
Industries We Serve
Domain-specific AI applications engineered around operational workflows and regulatory standards.
Our Approach
Assess
Identify high-ROI use cases and check data and AI readiness.
Prepare data
Clean, connect and govern the data your models depend on.
Prototype
Working proof-of-concept in weeks, evaluated against real metrics.
Productionize
Secure, observable, scalable deployment integrated with your systems.
Govern & improve
Monitoring, evals, guardrails and continuous fine-tuning.
Built Responsibly
Guardrails
Input/output filtering, PII redaction and policy enforcement on every call.
Explainability
Traceable reasoning, citations and audit logs for every AI decision.
Human in the loop
Review and approval steps where the stakes are high.
Continuous evals
Automated quality, bias and regression testing before and after release.
Start your Generative AI journey.
Get a working prototype in as little as 6 weeks.
Generative AI FAQs
We implement hybrid search (dense vectors + BM25), contextual parent-chunk retrieval, cross-encoder reranking (Cohere/BGE), and self-reflective hallucination guardrails.
Never. We deploy private tenant endpoints on AWS Bedrock, Azure OpenAI, or self-hosted open models (Llama 3/Mistral) with zero-retention data policies.
We use multimodal layout parsers to preserve table structures, headings hierarchy, and embedded figures in vector embeddings.
We automate continuous Ragas and TruLens evaluations measuring Faithfulness, Answer Relevance, Context Precision, and Context Recall.