tacitlabs.ai
Organisational Cognition Infrastructure.
Every organisation runs on two operating systems. The official one is documented. The real one — what your experts actually do — has never been captured by any technology. We build the infrastructure to change that.
- We capture the invisible expertise that makes your organisation actually work.
- Behavioural analytics + knowledge graph + intent engine — built for regulated enterprises.
- Your AI doesn't fail because the models are bad. It fails because it doesn't know what your best people know. We fix that.
awareness.problem.1.0 the problem nobody talks about
Your best experts are retiring. Their judgment is worth millions.
None of it is written down.
A single departing senior underwriter costs £1.75M–£7.6M
in lost institutional knowledge. Training a replacement takes
5–10 years. The pipeline is empty.
Meanwhile, 88% of enterprises have adopted AI. Only 5% see
real returns. The gap isn't technology — it's the invisible
expertise your AI was never given.
— BCG + McKinsey, 2025
awareness.problem.2.0 the missing layer
Your best engineer diagnoses a failure before the logs catch up.
Your senior analyst sees the pattern in the data three weeks before the model does.
Your veteran operator knows which step to skip — and why it still works.
None of this is written down. It lives in their heads — heuristics built
over decades. When they leave, their expertise leaves with them.
Your AI doesn't fail because the models are bad.
It fails because it doesn't know what your best people know.
awareness.problem.3.0 the knowledge gap
AI agents are only as good as the knowledge you give them.
RAG, fine-tuning, prompt engineering — they're all ways to pour
explicit knowledge into a black box. They don't capture the how
or the why. They don't capture the expertise that makes
your organisation actually work.
awareness.thesis two operating systems
Every organisation runs on two operating systems.
The Official OS
—
Processes, models, dashboards, SOPs. Documented, measured, managed.
This is the operating system your board sees.
The Real OS
—
What your experts actually do. Why they override the model. When they
trust their gut over the data. The shortcuts that work. The exceptions
that matter. The judgment calls that make the difference between a
good decision and a catastrophic one.
The real operating system has never been captured by any technology.
Not ERP. Not CRM. Not BI. Not AI.
It lives in human minds — and it walks out the door every day.
Tacit is the first infrastructure layer designed to make the real
operating system visible, durable, and computable.
cognition.layers the knowledge hierarchy
Every system in your organisation — AI models, analytics,
training programmes — runs on explicit knowledge.
The expertise that actually drives outcomes sits below,
invisible and uncaptured. We go there.
guided.journey how it works
Week 1–2: Deploy
—
Observer SDK goes live as a browser extension across your expert
team. Zero disruption to existing workflows. The system begins
detecting override events, hesitation patterns, and decision
anomalies from day one.
Week 3–8: Extract
—
The system identifies override patterns and surfaces heuristic
candidates. At key decision moments, experts confirm or refine
the logic the system has inferred. Output: validated expert rules
your models have never seen.
Month 2–4: Codify
—
The knowledge graph populates with expert heuristics — each
tagged with conditions, confidence scores, and outcome data.
Your AI systems start using expert reasoning instead of
generic priors.
Ongoing: Compound
—
Continuous capture feeds models, the graph deepens, new
heuristics are auto-discovered. You get visibility into where
AI behaviour diverges from expert judgment — and the gap closes
permanently.
To see the full technical architecture — data flows, components, and deployment
patterns — read the architecture overview ↗.
timing why now
The workforce cliff is here
—
10,000 baby boomers retire every day across the US and UK.
Expert-dependent industries — engineering, finance, legal,
healthcare — are dominated by professionals aged 50+. Their knowledge
is leaving faster than it can be transferred. Training a replacement
takes 5–10 years. The pipeline is empty.
LLMs made extraction possible
—
Before 2023, encoding unstructured expert reasoning into machine-readable
form was a research problem. Foundation models can now parse natural
language heuristics, classify decision patterns, and generate structured
knowledge representations. The core technology bottleneck has lifted.
Regulators are demanding explainability
—
The EU AI Act (2025), emerging US AI governance frameworks, and
sector-specific regulations all mandate that organisations explain
how AI-assisted decisions are made. If your experts' decision logic
isn't documented, you have a compliance gap today.
$1.8 trillion in AI investment by 2030
—
Companies are racing to deploy agents, but without the right knowledge
layer, they're building expensive automation on fragile foundations.
The window to capture tacit knowledge before it walks out the door
is closing rapidly.
Four forces converging: expertise is leaving, extraction is now
technically possible, investment is flooding in, and regulators demand it.
The window is 18–36 months before the knowledge is gone permanently.
proof the ground reality
reality
Experienced underwriters override model recommendations
25–40% of the time — and outperform the model in 85%+
of those cases. That logic has never been captured.
—
Insurance industry analysis
cost
10,000 baby boomers retire every day across the US and UK.
Each departing expert carries £1.75M–£7.6M in undocumented
decision logic. Training a replacement takes 5–10 years.
—
Deloitte + LIMRA
gap
85% of AI projects never reach production.
84% of enterprises haven't redesigned workflows for AI.
The missing piece isn't technology — it's the expertise
layer nobody has captured yet.
—
Gartner + Deloitte
market
Enterprise knowledge management market: $1.2T by 2032.
Organisations know expertise is their moat. They just can't
capture the most valuable part of it — yet.
—
Grand View Research
vertical.domains industries
Every expert-dependent industry has the same problem: the most
valuable knowledge has never been captured. We start where the
expertise concentration risk is highest.
Insurance
Underwriting · Model Overrides · Risk
Assessment
Explore →
Credit Risk
Credit Committees · Model Overrides · Loss
Provisioning
Phase 3
Clinical Decision Support
Diagnosis · Treatment Pathways · Triage
Phase 3
Energy & Engineering
Anomaly Detection · Maintenance ·
Operations
Phase 4
solution what we are — what we are not
| Category | What They Do | What We Do |
|---|---|---|
| Knowledge Management | Confluence and SharePoint capture what people write down. | We capture what they can't articulate. If your best expert could put everything they know into a wiki, you wouldn't need us. They can't. That's the point. |
| RAG | Retrieval-augmented generation retrieves existing documents. | The most valuable knowledge in your organisation has never been written down. RAG retrieves nothing. We create the knowledge that RAG should be retrieving. |
| Process Mining | Celonis tells you that your best operator takes three extra steps. | We tell you why they take those steps — and why those steps are the reason they're your best operator. |
| Decision Intelligence | Palantir builds intelligence from data. They start top-down with transactions. | We build intelligence from expertise. We start bottom-up with people. Complementary — not competitive. |
Before you can manage knowledge, you have to capture it.
Before RAG can retrieve expert judgment, someone has to extract it.
We're building organisational cognition infrastructure — the layer
that makes the invisible intelligence of your organisation visible,
durable, and computable.
convergence.thesis the future of AI
The Future of AI Is Not General.
It is specialised and adaptive.
The most powerful AI systems will not be trained on the internet. They will
learn from domain expertise and real-world decisions — the invisible
intelligence that lives inside your organisation.
Tacit provides the infrastructure that connects them.
Together, they create Organisational
Superintelligence.
prove.first the pilot programme
3 experts. 90 days. We extract heuristics, validate them,
and demonstrate measurable improvement in model-expert
agreement.
What you get
—
A validated knowledge graph of expert rules your models
have never seen. Quantified model accuracy improvement.
Documented expert override patterns with conditions and
confidence scores. A clear business case for full deployment.
What it costs
—
Outcome-based pricing. No multi-year lock-in. If we don't
discover rules your models don't know, you pay nothing.
We don't ask you to believe. We ask you to measure.
engage start a conversation
30 minutes. We assess fit — your decision complexity,
expert concentration risk, and AI maturity. No pitch deck.
Mutual evaluation.
Capacity-limited by design. We partner deeply with 3–5 enterprises
at a time. No surface-level deployments.
© 2026 Tacit Labs. Organisational Cognition Infrastructure.