The Problem
Your Business Data Is a Goldmine. Nobody Can Find the Gold.
Enterprises sit on decades of operational data — CRM records, SQL databases, ERP transactions, support tickets, billing histories. Yet 80% of it is completely invisible to AI. This is the dark data problem, and it costs millions.
80%
of enterprise data is dark — invisible to any AI model
£10M+
typical failed DXP migration cost (Sitecore, Adobe, Optimizely)
20
person data-entry teams doing work that should be automated
18 months
average enterprise integration project before any value
The Sitecore Lesson: What £10M Buys You
Paul Maddison spent years in the Sitecore ecosystem — including helping build Webuyanycar, one of the UK's most recognised brands. He saw first-hand what happens when enterprises bet everything on monolithic DXP platforms:
- 1Promised omnichannel personalisation, delivered a CMS with a learning curve
- 2£2M–£10M implementation costs before a single customer saw a difference
- 318-month timelines that ballooned to 3 years
- 4Vendor lock-in so deep that migrating away cost as much as the original build
- 5The ‘headless’ pivot came too late — customers had already lost faith
- 6Data sat in Sitecore’s silo, disconnected from CRM, ERP, and actual business context
The AI Wrapper Bubble
Thousands of startups have launched AI-labelled tools that are little more than a thin interface on top of GPT-4. They have no proprietary data, no defensible moat, and no enterprise governance story. When OpenAI, Anthropic, or Google add the same feature natively, these wrappers evaporate overnight.
Why KynticAI Is Not a Wrapper
KynticAI does not wrap AI models — it feeds them. The Universal Context Layer sits below any model (GPT, Claude, Gemini, Llama, Mistral) and above your existing data systems. It is the governed semantic substrate that turns raw business data into structured, AI-ready context with full provenance and confidence scoring. The more models that connect, the more valuable the context layer becomes.
The Fear Trifecta
Every enterprise CEO we speak to voices the same three fears about AI adoption.
Existential Fear
If we don’t adopt AI, our competitors will. But if we adopt it wrong, we’ll waste millions and lose trust.
Sovereignty Fear
Our data cannot leave our servers. NHS, MoD, financial services — regulators won’t allow US cloud dependency.
Proof Fear
Every vendor promises transformation. Buyers need an evidence-led pilot plan before they commit to another broad technology programme.
Friction vs Lift
Every legacy approach adds friction. KynticAI replaces friction with measurable lift.
| Friction (Legacy) | Lift (KynticAI) |
|---|---|
| 12–18 month integration timeline | Scoped pilot path, context map in days |
| Requires data warehouse first | Reads data where it already lives |
| Manual ETL pipelines | Automated semantic selectors |
| Static reports decay instantly | Self-improving context, daily learning |
| Per-seat licensing £150k+/year | Value-based pricing tied to ROI |
| US cloud dependency | On-prem sovereign deployment |
| No attribution model | Conversion attribution to selector level |
| Hope-based ROI | Discovery Agent pilot brief |
Live Intelligence
What Dark Data Actually Costs
Illustrative blind spots showing why a governed context layer matters before model rollout.
Industrial Supplies — Magento 2, SQL Server, £140M revenue
£284k/year at risk
“Trade account Henderson Plumbing (£284k annual spend) has not placed an order in 34 days — their average reorder cycle is 12 days. Last 3 emails from their buyer went unanswered. Portal login frequency dropped from 8x/week to once in the last fortnight. Churn risk: 91%. This account represents 3.3% of total revenue.”
Law Firm — 280 lawyers, Dynamics 365 + iManage + SQL billing
£480k at risk
“Client Whitfield Industries (£480k annual billings) shows 3 consecutive churn signals: billing volume down 42% over 6 months, partner email response time increased from 1.2 to 3.8 hours, and a new conflict check shows they’ve instructed a competitor firm. Churn probability: 87%.”
Grocery Chain — 48 stores, ERP + POS + loyalty
£8,200/week saved
“Store 14 (Warrington) is projecting 340 units of fresh bakery waste this week — 2.8x the chain average. Root cause: a local school half-term means footfall is down 31% but the automated replenishment order was placed before the pattern was detected. Projected waste saving: £8,200 this week.”
Stop Fighting Your Data. Start Using It.
See how KynticAI solves these problems at the architecture level.