KynticAI

The Universal Context Layer for Enterprise AI

Your data, your firewall, any AI model.

Most systems were designed to manage work, not empower.

KynticAI turns existing business systems into governed, AI-ready context without forcing a replatforming programme or copying raw operational data into another vendor cloud.

Existing systems

SAP, Postgres, SQL Server, CRM, SharePoint, flat files

Universal Context Layer

Selectors, provenance, confidence, freshness, semantic facts

Any AI model

Briefed with governed business context instead of copied raw data

Quietly different

KynticAI makes the data layer useful to the model layer.

Most AI programmes fail at the join between business systems and model prompts. The Universal Context Layer is that join: semantic, auditable, customer-owned, and designed by an Enterprise Architect with 26 years across commercial data platforms.

We are not another AI wrapper

KynticAI sits below the model layer. It gives models the governed context they need, without pretending the model is the product.

No rip-and-replace ceremony

The context layer is designed to read the stack an enterprise already has, then build semantic facts with provenance and confidence.

Built for regulated buyers

NHS, defence, financial services, and other sensitive environments need sovereignty by architecture, not a policy slide.

Production posture

Launch with the claims we can stand behind.

Sovereign by design

KynticAI reads metadata and context signals in the customer environment. The underlying records stay where they already live.

Model-agnostic

Serve governed context to GPT, Claude, Gemini, Llama, Mistral, or a customer-hosted model without binding the business to one AI vendor.

Open-core path

A public Scout core establishes the data-plane contract; private enterprise extensions add customer-specific connectors, identity, and governance.

Pilot-first selling

The commercial route is an honest paid pilot and customer-owned data plane, not a claim of finished self-serve SaaS before production validation.

The Old Way vs The KynticAI Way

The old wayThe KynticAI way
Copy data into a vendor cloudRead metadata and context signals in the customer environment
Build a warehouse before AI can startOverlay semantic selectors on the systems already running the business
Prompt a model with stale fragmentsServe governed context facts with provenance, confidence, and freshness
Lock strategy to one model vendorKeep the model replaceable and the enterprise context compounding
Buy on hope and wait for proofStart with a scoped discovery and pilot plan before broad rollout

Live Intelligence

Illustrative Context Scenarios

Example outputs showing the sort of governed business context KynticAI is designed to surface during a pilot. These are not customer claims.

Context scenario
E-Commerce & Retail

Multi-Channel Fashion Retailer — £85M revenue

£47k/month saved

SKU 8842 (Charcoal Wool Coat, size M) now shows a 31% online return rate versus 12% in-store. Customers who viewed the size-guide had 42% lower returns. Recommended action: add mandatory size-guide modal for this SKU and all lookalikes. Projected impact: £47k/month reduction in returns.
Context scenario
Manufacturing

Steel Producer — 3 blast furnaces, legacy SCADA + SQL Server 2014

£1.8M annualised saving

Blast Furnace 2 produced 0.3% higher defect rate over 72 hours. The Rust engine correlated this with a 1.4% increase in silica content in iron ore from Supplier Kongsvik. Recommended: blend remaining batch with Ironridge ore at 60/40 ratio. Projected impact: return defect rate to baseline, saving £1.8M annualised.
Context scenario
Healthcare

NHS Acute Hospital Trust — sovereign, on-prem

+14 procedures/week

Theatre 4 utilisation has fallen 18% over 11 days. Root cause is post-op ward 7B at 94% capacity plus 3 recovery nurses on long-term sick. Recommended: redirect morning slots to Theatres 2 and 3 until staffing recovers. Projected impact: +14 additional procedures per week.
Context scenario
Financial Services

Challenger Bank — 800,000 customers

4,200 accounts at risk

Customers who open a current account but don’t set up a direct debit within 14 days have a 63% probability of becoming dormant within 90 days. 4,200 customers are currently in this window. 78% opened the ‘Set Up Direct Debit’ screen but didn’t complete — suggesting UX friction, not lack of intent.

Ready to see what your systems already know?