Design. Build. Operate.
Data & AI that move the needle.

We apply AI where it pays off, forecasting and classic ML, computer vision, and agentic/RAG assistants delivered to production with guardrails and MLOps.

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AI Consulting & Application in Your Business

Use AI where it matters most. We audit processes and data, identify feasible use cases, and shape a roadmap with measurable KPIs.

Opportunity mapping & feasibility

Data / knowledge readiness review

KPI model (deflection, AHT, CSAT, FCR)

Architecture options across RAG, agent frameworks, ML, CV, RecSys and other components

Proof of Concept (Validate Hypotheses)

Quickly test value and risks before scaling. We deliver PoCs that prove retrieval quality, agent reliability, and ROI assumptions.

Retrieval / agent evaluation (quality, safety)

ML/CV signal validation (classification, detection, OCR)

Pilot plan & next-step architecture

Hypothesis design & success criteria

End-to-End Product Development

From prototype to production. We build assistants and agentic workflows that actually do the work across your stack.

RAG assistants for support & knowledge search

Agentic actions for CRM / tickets / orders

Computer vision for QA, document understanding, and ops

Quality evaluation, guardrails, governance

ML models for scoring, forecasting, routing

Integrate or Custom-Build

Plug into your ecosystem or ship custom pieces where needed.

Vector DBs & indexing pipelines

Observability for latency, quality, and cost

Connectors: CRM, telephony, wikis, confluence, data stores

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How we drive value

Reliable regional forecasts for sales, profit, cash flow – to guide budgets and cash decisions

NDA, EU, FMCG

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See what we’ve shipped in production

AI Learning Assistant for a Global Bank

NDA, EU, Global Bank

Explore real examples of AI agents, RAG assistants, ML scoring, and CV pipelines delivering measurable impact – from self-service deflection to agentic process automation. 

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Focused on outcomes since early 2023

Governance, compliance, and run-costs are built in from day one.

We deploy AI where it moves P&L: lower support costs (deflection, AHT), faster cycle times in sales and ops, and higher self-service and conversion.

We design for time-to-value, build on your stack, and measure impact in hard KPIs and not demos. When ML, CV, or RecSys lift results, we add them pragmatically; when they don’t, we don’t.