LLMs & NLP
RAG, chatbots, summarization, redaction, evaluations, prompt ops.
We help you identify the highest-ROI AI use cases, prototype quickly, and deploy with solid MLOps, governance, and change management.
We design and scale Lakehouse solutions: Delta Lake optimization, Unity Catalog governance, MLflow experiments/registry, and production MLOps on Databricks SQL & Workflows.
End-to-end services—from strategy to production.
RAG, chatbots, summarization, redaction, evaluations, prompt ops.
OCR, defect detection, IDP, medical imaging, retail analytics.
Feature stores, CI/CD for ML, monitoring, governance & security.
Workflow copilots, content automation, code assist, knowledge search.
Member 360, prior auth, claim fraud, clinical summarization.
Risk scoring, KYC/AML, claims triage, forecasting.
Demand planning, shelf vision, personalized offers.
Case processing, document AI, citizen support.
Align on goals, data landscape, and constraints. Prioritize use‑cases by ROI and feasibility.
Rapid POCs in 2–4 weeks: measurable KPIs, evaluation harness, stakeholder demos.
Harden pipelines, add monitoring, security, and CI/CD. Prepare for scale.
Rollout + enablement. Train teams, integrate with workflows, track ongoing ROI.
AWS · Azure · GCP
Databricks (Lakehouse, Unity Catalog) · Snowflake · BigQuery
OpenAI · Azure OpenAI · Anthropic
MLflow · KServe · LangChain
Discovery can kick off in 3–5 business days once we align on scope and access.
Yes—architectures support HIPAA/PHI with least‑privilege access and audit trails.
We offer both. Pilots are often fixed‑bid; long‑term builds are T&M with milestones.
Tell us your goals. We’ll map use‑cases and a delivery plan.