Knowledge & Insight · Use Case Hub

Automate Knowledge Management with AI

How to automate knowledge management with AI across 42 industries. Workflow design, AI agents, governance, and the KPIs (search success, time saved, knowledge freshness, and repeated question reduction) we report on weekly. Pick your industry below for a scoped engagement.

Early access: we work with a small first cohort. Engagements are scoped, priced, and shipped end-to-end by our team — not referred to third parties.

Primary outcome

make institutional knowledge searchable and actionable

What we ship

knowledge graph, retrieval assistant, content governance, and freshness workflow

KPIs we report on

search success, time saved, knowledge freshness, and repeated question reduction

What "automating knowledge management with AI" actually means

Automating knowledge management with AI is not a single product you buy. It is a workflow you redesign around AI as the operating layer. The agent handles the high-volume, high-structure tasks. Humans handle edge cases, exceptions, and trust-sensitive decisions. The system is instrumented to measure search success, time saved, knowledge freshness, and repeated question reduction and improve weekly.

What changes by industry is the systems the agent integrates with, the data it retrieves over, the controls it operates under, and the KPIs it has to defend. The architecture is similar; the integration and the controls are different.

The architecture we use for AI knowledge management

  • Frontier LLM — Claude, GPT-4-class, or Gemini. We benchmark candidates on a labelled test set during Discovery.
  • Retrieval layer over your approved internal sources, with source citations on every output.
  • Tool use for reads and writes against your operational stack (CRM, ERP, ticketing, data warehouse).
  • Reviewer queue for low-confidence outputs. Confidence thresholds set per workflow.
  • Evaluation harness — labelled test set, weekly accuracy reports, regression alerts.
  • Versioned prompts and reviewer-action audit logs for traceability.

Pick your industry

42 industries. Each industry page is a scoped engagement with industry-specific systems, controls, and pricing.

Commerce

Energy

Financial Services

Food and Agriculture

Food and Hospitality

Healthcare

Manufacturing and Industrial

Manufacturing and Mobility

Media

People Operations

Professional Services

Public and Knowledge Services

Public and Social Impact

Public Sector

Real Assets

Supply Chain

Technology

Technology and Communications

Travel and Hospitality

Travel and Mobility

Frequently asked questions

How do you automate knowledge management with AI?+

We map your existing knowledge management workflow, identify high-volume and high-structure tasks, build an AI agent that handles those tasks, and route low-confidence cases to a human reviewer. The build connects to the systems your industry already runs on, runs against a labelled test set, and ships behind a reviewer queue before it sees production traffic. We measure search success, time saved, knowledge freshness, and repeated question reduction from day one and improve weekly.

What is the best AI agent for knowledge management?+

There is no single off-the-shelf "best" agent for knowledge management — the right architecture depends on the systems and data of your industry. We typically combine a frontier LLM (Claude, GPT-4-class, or Gemini) with a retrieval layer over your approved sources, tool-use for your stack, and a reviewer queue. We benchmark candidates against a labelled test set during Discovery and pick the model with the best accuracy/cost ratio.

What does AI knowledge management cost?+

Three phases, billed separately. Discovery sprint: $6k. Build engagement: $22k–$30k. Run retainer: $3k–$5k / mo. ~$34k–$60k typical year 1 (60% take the run option for ~6 months). Pricing varies slightly by industry — see the industry-specific pages below.

How long does it take to deploy AI knowledge management?+

Thin-slice in production in ~6 weeks after Discovery, full Build phase over 7-10 weeks. By day 90, search success, time saved, knowledge freshness, and repeated question reduction is instrumented and you have a baseline against which to expand to adjacent workflows.

Which industries do you build AI knowledge management for?+

All 42 industries listed below. Each industry has its own scoped engagement page with industry-specific systems, controls, and KPIs. Common starting industries include Airlines, Airports, Hotels, Travel Agencies, Banking, and others.

What do we own, and what do you own?+

We own workflow design, prompts, retrieval architecture, evaluation harness, and weekly improvement. You own data access, policy, exception approval, and final commercial decisions. At the end of the engagement, every prompt, eval, and config is handed over — no lock-in.

Start the engagement

Book a discovery call for AI Knowledge Management

Tell us about your workflow, the systems involved, and the KPI you want to move. We'll send a scoped statement of work within 5 business days.