From a first pilot to a governed, monitored deployment your team runs without us. Automation, agents, private deployments, and the data and semantic foundations that make their answers trustworthy.
Strategy, foundations, build and governance — the whole path, not just the model.
AI Process Automation
Take the repetitive work off your team’s plate.
Every team has work that runs on copy and paste: rekeying between systems that were never integrated, chasing approvals, rebuilding the same report every week. We map those workflows, automate the parts that are genuinely rule-based, and put monitoring and guardrails around the rest — so the automation keeps working when a source system changes, instead of failing quietly and sending everyone back to the spreadsheet.
Twenty years of building the pipelines and integrations these workflows run on.
Autonomous Agent Development
Agents that act in your systems, not just answer questions.
A chatbot answers questions. An agent does the work — reads the request, checks the record, updates the system, and escalates when it is not sure. We design the tool integrations, the permissions, and the confidence thresholds that decide when an agent proceeds on its own and when a person takes over, so its autonomy is bounded by something more deliberate than optimism.
Grounded in the data engineering and systems integration behind 800+ delivered projects.
AI Training Workshops
Capability that stays after we leave.
Most AI training is a single session that leaves people impressed and unchanged. We size the curriculum to the role, because what an analyst needs is not what a director needs, and run it hands-on against your own data and tools rather than a generic sandbox. Recurring follow-up sessions catch the real questions, which surface weeks later when someone is stuck on their own work.
Delivered the way our enablement practice runs: structured courses, recurring office hours, and working sessions against your own use cases.
AI Strategy
A funded, sequenced plan — not another proof of concept.
AI programs stall in a pile of pilots that never reach production, because nobody agreed what success looked like or who owned the budget. We establish where you actually stand, identify where AI creates value in your business specifically rather than in general, and prove it with a pilot under production conditions. You are left with a sequenced, costed roadmap and the governing body to keep it moving.
Built on our Aligned Enterprise Operating Model™ and APEX Prioritization Model™.
AI Governance & Model Risk
Prove your AI is controlled — to your board, your auditors, and your regulators.
Most organizations can’t answer basic questions about the AI already running in their business: which models are in production, what data trained them, who can retrieve what. We build the model inventory, input lineage, and access controls that turn that uncertainty into evidence — mapped to the frameworks your examiners actually cite.
Built on Collibra and Alation, with 20 years of lineage work behind it.
Private & Sovereign AI
Enterprise AI that never leaves your environment.
If your data can’t go to a third-party API, most AI vendors have nothing to sell you. We deploy production AI inside your own cloud tenant or data center — your models, your infrastructure, your controls, no external inference calls. Start with a fixed-price pilot and a defined use case, not an open-ended platform commitment.
For teams where data residency, client confidentiality, or contractual restrictions rule out the obvious options.
Most failed AI pilots fail at retrieval, not reasoning. Contracts, policies, credit memos, service tickets, and knowledge bases were never inventoried, permissioned, or quality-checked — so the model retrieves the wrong thing and answers confidently. We make unstructured content AI-ready: source inventory, metadata enrichment, chunking and retrieval design, permission inheritance, and quality scoring on the corpus itself.
The same data quality discipline we’ve applied to enterprise data for two decades, pointed at the 80% that was never in a database.
Natural Language Analytics
Ask in plain language. Get an answer you can put in front of the board.
Chat-with-your-data demos work beautifully until the tool is asked about your revenue, your margin, your churn — and returns a number nobody recognizes. The gap is the semantic layer: governed metric definitions, business logic, and relationships the model can’t infer on its own. We build that layer and connect it to your AI interface, so answers reconcile with your reporting instead of competing with it.
Dimensional modeling and semantic layer design across 200+ implementations, applied to Snowflake Cortex, Microsoft Fabric, and Copilot.
The value
Intelligent automation, measurable ROI
Transform operations with automation that streamlines workflows, reduces errors, and drives efficiency — while future-proofing how you work.
Operational ExcellenceStreamlined, reliable workflows that scale.
Cost EfficiencyUp to 60% lower operational cost.
Workforce EmpowermentTeams focused on judgment, not busywork.
Competitive EdgeMove faster than wait-and-see peers.
Our AI Readiness Scorecard evaluates your organization across 7 critical pillars — from Executive Sponsorship to Technical Infrastructure — and delivers a clear implementation roadmap, instantly.
