What We Build
RAG Pipelines
Retrieval-Augmented Generation systems that give LLMs accurate, up-to-date context from your own documents and databasesreducing hallucination to near zero.
AI Assistants & Chatbots
Product-embedded AI assistants that answer user questions, navigate workflows, and complete tasks using your product's data and APIs.
Document Intelligence
Extract structured data from contracts, invoices, forms, and reportsautomated document processing at scale.
LLM-Powered Automation
Replace manual, high-volume cognitive tasks with AI agentscontent generation, data enrichment, email triage, and more.
Models & Infrastructure
LLM Providers
OpenAI GPT-4o, Anthropic Claude, Google Gemini, Meta Llama (self-hosted), Mistral
Vector Databases
Pinecone, Weaviate, Qdrant, pgvectorwe select the right one for your data scale and query patterns
Orchestration
LangChain, LlamaIndex, custom orchestration layers for complex multi-step agent workflows
Cost Control
Token budgeting, caching strategies, and model routing to keep AI feature costs predictable
Production Readiness
Evaluation & Testing
Automated LLM evaluation pipelines with quality metricsso regressions are caught before they reach users.
Safety & Guardrails
Input/output filtering, content moderation, and prompt injection protection for enterprise use.
Observability
LLM-specific monitoringlatency, cost per query, quality scores, and conversation analytics.
Fine-tuning
Domain-specific fine-tuning when RAG isn't enoughcustom models on your proprietary data.