Capabilities

Retrieval-Augmented Generation

We build RAG systems that perform consistently in production — not just in demos. That means rigorous evaluation harnesses, drift detection, and data contracts between your pipeline components.

• —Retrieval pipeline design (hybrid search, re-ranking, chunking strategy)
• —Evaluation frameworks: faithfulness, relevancy, context precision
• —Drift detection and automated regression alerting
• —Data contracts for document freshness and schema drift
• —Observability dashboards and cost monitoring

Agentic Systems

Multi-agent orchestration is powerful and fragile. We design agent workflows with explicit state machines, guardrails, and observability so you can trust what's running in your infrastructure.

• —Multi-agent workflow design and orchestration
• —Tool use, function calling, and API integration
• —Guardrail design: input validation, output filtering, circuit breakers
• —Human-in-the-loop escalation patterns
• —Tracing, logging, and cost attribution per agent step

Data Engineering

AI is only as good as the data feeding it. We build the pipelines, knowledge graphs, and entity resolution systems that make your data a reliable foundation.

• —Entity resolution: deterministic + probabilistic + LLM-assisted
• —Knowledge graph construction and maintenance
• —Data pipeline design for ML feature stores
• —Data quality monitoring and alerting
• —Vector database selection, indexing, and maintenance

LLM Integration & Evals

Choosing and integrating LLMs requires more than picking the highest benchmark. We help you select, evaluate, and integrate models with rigor — including fine-tuning when warranted.

• —Model selection and benchmark analysis for your use case
• —Prompt engineering and prompt management systems
• —Fine-tuning strategy: when to fine-tune vs. prompt
• —Evaluation framework design and baseline tracking
• —Cost optimization: caching, routing, and batching strategies

AI Infrastructure

From model serving to MLOps, we set up the infrastructure that lets your AI systems scale and evolve without constant firefighting.

• —Model serving architecture (batch, streaming, real-time)
• —MLOps pipeline design and CI/CD for model updates
• —Observability stack: tracing, metrics, alerting
• —Infrastructure-as-code for reproducible deployments
• —Cost monitoring and optimization frameworks

Automation & Workflow

Beyond AI, we automate the data workflows and business processes that free your team to focus on higher-leverage work.

• —Document processing and intelligent data extraction
• —Automated reporting and insight generation
• —Integration with CRMs, ERPs, and internal tools
• —Workflow orchestration with Airflow, Prefect, or custom solutions
• —API design for AI-powered internal tools