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What Happens During the Call

Rapid-fire context download – current goals, blockers and data stack.

Use-case triage – blitz through possible AI initiatives, rate them by impact vs. feasibility, and shortlist the top 2-3 wins.

Execution roadmap sketch – phases, KPIs, and team skills needed for the first 90-day sprint and the 12-month vision.

Next-step commitments – agree on immediate actions, optional follow-up support, and investor-ready talking points.

You’ll Walk Away With

A one-page PDF summary (sent within 24 hrs) capturing priorities, architecture hints, and a 90-day action grid.
A scored use-case backlog—impact, effort, and risk flags for each idea we discuss.
My candid take on whether you should build, buy, or politely ignore that hyped-up tech everyone else is chasing.

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Service Title

Turning a “generic RAG chatbot” into a product with a moat

Brief Description :

Got a proof-of-concept chatbot that searches a vector store and spits out answers? I’ll help you turn it into an enterprise-ready product with a moat:

Always-fresh knowledge graph – nightly drift detection and delta re-embedding keep answers current without blowing your token budget.
Brand & compliance shield – real-time tone checker and banned-phrase scrubber ensure every reply sounds like you and leaks nothing.
Explainable UX – inline citations, auto-charts, and optional 30-second voice summaries build trust with non-tech users.
Plug-and-play connectors – out-of-the-box sync for Confluence, SharePoint, Salesforce, and GitHub (no more manual PDF uploads).
ROI dashboard – time-saved metrics, answer-reuse heat-map, and topic gaps your leadership will love.
LLM-Ops layer – canary QA, drift alerts, and regression tests so quality never silently degrades.

Book a session and walk away with a tailored roadmap—tech stack recommendations, architecture diagram, and a 10-day rollout plan.

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Francis A

Chatbot into a moat