AI & Intelligent Automation
Production-ready AI systems that connect company knowledge, data and workflows.
We build digital workers, not demos: AI agents and intelligent automation wired into the systems you already run, acting under explicit guardrails — with humans in control of consequential decisions.
AI value comes from redesigned workflows, not deployed tools.
Most AI initiatives stall between a promising demo and a system people actually trust with real work. The gap is engineering: integration with your data and systems, evaluation against real cases, and governance that makes automation accountable.
What this service covers.
AI Agents & Automation
- Multi-agent workflow design
- Document and process automation
- Task orchestration across systems
- Autonomous actions under explicit guardrails
Enterprise Knowledge & RAG
- Retrieval-augmented generation over internal corpora
- Knowledge base structuring and chunking strategy
- Semantic search and reranking
- Source attribution and citation trails
Systems Integration
- ERP, CRM and ticketing connectors
- API and webhook integration layers
- Event pipelines and job orchestration
- Identity-aware data access
Evaluation, Governance & Observability
- Evaluation harnesses and golden test sets
- Human-in-the-loop approval gates
- Cost, latency and quality telemetry
- AI usage policy and NIST AI RMF alignment
From first scope to steady state.
We map workflows, data and decision points to find where AI creates measurable leverage — and where it doesn't belong.
- Workflow mapping
- Opportunity scoring
- Data readiness
- Risk screen
What you receive.
Architecture, evaluation and governance documentation for the teams who will run the system after we hand it over.
AI opportunity map
Solution architecture
Working prototype on real data
Evaluation framework and test sets
Production integration with guardrails and monitoring
AI usage policies and human-in-the-loop design
From a working prototype to automation your team can operate, evaluate and audit.
- Baseline
- Guardrails
- Rollout
- Monitoring
Standards we assess and implement against.
Standards we assess and implement against when putting AI into production.
- NIST AI Risk Management Framework
- ISO/IEC 42001 (AI Management System)
- OWASP Top 10 for LLM Applications
- ISO/IEC 27701 (Privacy)
- Data access and retention controls
- OpenAI / Anthropic / open-weight models
- LangGraph & agent frameworks
- Vector databases & RAG stacks
- Evaluation and observability tooling
Ways to start.
AI Discovery Sprint
2–4 week engagement mapping workflows, scoring opportunities and delivering a prioritized roadmap with a working prototype.
Best for: Organizations deciding where AI is worth investingBuild & Integrate
Fixed-scope delivery of a production agent or automation, integrated with your systems and governance.
Best for: Teams with a validated use case ready for productionAI Operations Retainer
Ongoing evaluation, monitoring, cost optimization and improvement of your AI systems.
Best for: Companies running AI in productionOther services.
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