Enterprise Knowledge Intelligence
Every organisation’s most valuable asset is what it already knows — and most of that knowledge is trapped in documents, emails, and people’s heads. This accelerator builds an intelligent knowledge platform that makes your institutional expertise searchable, actionable, and continuously learning. In 10 weeks.
The Problem
Critical insights are buried across dozens of disconnected systems — SharePoint, Google Drive, Slack, ERPs, filestores. Finding the right expert or the right document takes hours or days. New starters take months to get up to speed because institutional knowledge isn’t accessible. Teams duplicate work because they can’t find what’s already been done.
Meanwhile, sensitive data is flowing into public AI tools because staff have no secure internal alternative. And knowledge walks out the door every time an experienced colleague leaves.
McKinsey solved this for themselves with “Lilli” — a generative AI platform giving 43,000 consultants instant access to nearly 100 years of institutional knowledge. Over 75% of staff use it monthly, saving 30% of research and synthesis time. But they spent 11 months and a team of 150+ to build it.
We help you build a right-sized version — tuned to your business — starting with a 10-week MVP.
RAG Chatbot vs. Knowledge Orchestration Platform
| Capability | Basic RAG | Knowledge Orchestration Platform |
|---|---|---|
| Document search | Single vector database | Multiple knowledge sources coordinated |
| AI models | One LLM | Multiple large and small models, task-matched |
| Document types | Text-heavy files only | PowerPoint, PDF, spreadsheets, images, transcripts |
| Expert matching | Not available | Connects queries to internal subject matter experts |
| Company tone | Generic outputs | Tuned to your organisation’s voice and standards |
| Security | Basic API key auth | Role-based access, audit trails, zero-trust architecture |
| Task automation | Answer questions only | Agents that draft proposals, create slides, summarise meetings |
| Intent understanding | Keyword/semantic matching | Context-aware routing based on your business domains |
What We Build
Knowledge Audit & Orchestration Layer
- Map every knowledge source in your organisation and assess what’s AI-ready
- Build a routing and coordination system that connects the right query to the right knowledge source using the right AI model
- Custom document parsing for your actual content — PowerPoint decks, PDFs, spreadsheets, and legacy formats
Expert Matching & Company-Tuned Outputs
- Integration with your people directory so the platform recommends who to speak to, not just what to read
- Fine-tuning so responses match your organisation’s tone, terminology, and quality standards
- Security and governance — role-based access controls, audit logging, and data residency compliance from day one
Specialist Agents
- Task-specific AI agents that go beyond Q&A — proposal drafting, meeting summarisation, onboarding assistant
- Intent classification and domain-aware routing for complex queries
- Continuous learning loop that improves results based on user feedback
Before & After
| Metric | Before | After | Improvement |
|---|---|---|---|
| Time to find knowledge | Hours to days | Seconds to minutes | 90%+ reduction |
| New starter ramp-up | 3–6 months | 4–8 weeks | 60% faster |
| Duplicate work | Common, undetected | Flagged and prevented | Significant reduction |
| Knowledge retention | Lost with the person | Captured and searchable | Institutional resilience |
| Shadow AI exposure | Uncontrolled | Secure internal alternative | Risk eliminated |
| Research & synthesis time | Baseline | 30% reduction | 30% time savings |
10-Week Implementation
Three phases. Ten weeks. One working platform.
Discovery & Architecture
- Week 1: Knowledge audit — catalogue all knowledge sources, document types, access patterns, and pain points
- Week 2: Data readiness assessment — evaluate quality, security, tagging, and bias across priority sources
- Week 3: Architecture design — orchestration layer blueprint, model selection strategy, security framework
MVP Build
- Week 4: Core orchestration engine — intent classification, query routing, multi-source retrieval
- Week 5: Document parsing pipeline — custom ingestion for your content types
- Week 6: AI model integration — response generation and quality checks
- Week 7: Expert matching & specialist agents — people directory integration plus 2–3 task agents
- Week 8: Security hardening — role-based access, audit trails, governance, and compliance
Launch & Transfer
- Week 9: Pilot deployment with power users, feedback collection, and iterative refinement
- Week 10: Wider rollout, adoption programme launch, monitoring setup, and knowledge transfer
Adoption: The Make-or-Break Factor
McKinsey’s experience proves that building the platform is only half the battle. Their adoption strategy — leadership role modelling, workflow integration, and user communities — drove 75% monthly active usage. We build that same adoption rigour into every engagement.
- Leadership role modelling — senior sponsors asking “Have you used the platform today?” at every meeting
- Integration into existing workflows — not a separate tool, but embedded in how people already work
- User communities — local groups sharing tips, use cases, and feedback
- Training woven into onboarding — new joiners learn the platform from day one
- Measurement tied to outcomes — usage becomes part of performance conversations
Who This Is For
- Organisations with 200+ employees and significant institutional knowledge
- Knowledge-intensive sectors — professional services, financial services, healthcare, manufacturing, retail
- Companies already seeing “shadow AI” usage with public tools like ChatGPT
- Organisations that want to turn proprietary knowledge into a competitive advantage
- Teams that need strict data governance and security standards
What Makes Our Approach Different
- We start with your business problem, not the technology
- We build an orchestration platform, not a basic RAG wrapper
- We design for adoption, with change management built into every phase
- We keep experiments cheap — the 10-week MVP proves value before you commit to scale
- We transfer knowledge, so your team can maintain and extend the platform independently
- We’re model-agnostic and platform-agnostic — we recommend what fits, not what we’re partnered with
Ready to Get Started?
A 30-minute discovery call is all it takes to work out whether this accelerator is the right fit for your organisation.