Accelerators

Engineering assets, not slideware.

Hardened components we reuse across programmes so your team spends its time on the domain, not the plumbing.

Accelerator

Design, evaluate and operate governed agents against real enterprise tools.

Solves: Agent prototypes stall because permissions, testing and observability are missing.
Architecture: Tool registry, policy engine, evaluation harness, trace store.
Integrations: ERP, CRM, ITSM, Identity provider
Implementation: 6–10 weeks to first supervised agent in production.
Governance controls: Scoped permissions · Approval thresholds · Full traces

Accelerator

Entitlement-aware retrieval across every enterprise knowledge source.

Solves: Copilots answer without provenance or respect for access rights.
Architecture: Connectors, hybrid index, re-ranking, citation service.
Integrations: SharePoint, Confluence, Object storage, Ticketing
Implementation: 4–8 weeks to a governed knowledge surface.
Governance controls: Entitlement propagation · Citation enforcement · PII redaction

Accelerator

Turn high-volume documents into validated structured data.

Solves: Manual keying and review dominate document-heavy processes.
Architecture: Layout parsing, extraction models, confidence routing, review UI.
Integrations: ECM, Workflow, ERP
Implementation: 4–6 weeks per document family.
Governance controls: Confidence thresholds · Human review queues · Accuracy monitoring

Accelerator

Asset health, quality and throughput intelligence across plants.

Accelerator

Inventory, risk-tier and monitor every model and agent in the estate.

Solves: No single view of what AI is running, where, and under whose approval.
Architecture: Registry, policy engine, evidence generator, monitoring feeds.
Integrations: Cloud AI platforms, GRC, SIEM
Implementation: 6 weeks to a governed inventory.
Governance controls: Risk tiering · Evidence packs · Continuous monitoring

Accelerator

Stand up a live twin for scenario simulation and optimisation.

Solves: Process changes are tested in production because no sandbox exists.
Architecture: Asset model, telemetry ingestion, simulation runtime, scenario UI.
Integrations: Historian, PLM, MES
Implementation: 10–14 weeks for a production-grade twin.
Governance controls: Model validation · Scenario audit · Safety limits

Accelerator

Repeatable pipeline for shipping evaluated GenAI applications.

Solves: Every new use case rebuilds the same scaffolding and controls.
Architecture: App templates, eval harness, prompt versioning, deployment pipeline.
Integrations: CI/CD, Model gateways, Observability
Implementation: 3–5 weeks to first application, days thereafter.
Governance controls: Evaluation gates · Prompt versioning · Cost budgets

Accelerator

Bring AI assistance into delivery without loosening quality gates.

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What should your enterprise be able to do next?

Tell us the outcome you want to achieve. We will help you identify, engineer and scale the right AI solution.