Sentrova Solutions

Services

AI-native systems for the work that keeps your organisation moving.

From one high-friction workflow to a connected operating system, we design and build practical AI, automation, data and software around the way your team actually works.

  • Zero lock-in
  • Governed by default
  • Built for production

Six workflow areas

Named accelerators where we have them. Custom builds where we do not.

These are proven patterns we configure and integrate around your systems, not a locked SaaS suite you adapt your workflow to fit.

Service & operations

Sentrova Resolve

Multi-channel support agent that triages requests, resolves routine enquiries and routes exceptions to a human queue.

Documents & records

Sentrova Flow

Extracts, validates and reconciles invoices, claims and manifests, with anomalies routed to a reviewer.

Knowledge & decisions

Sentrova Atlas

Permission-aware search across internal files, answering with traceable, page-level citations.

Revenue & customer workflows

Sentrova Convert

Qualifies inbound leads and books meetings the moment they arrive, logged straight to your CRM.

Data & reporting

Sentrova Signal

Watches event streams and business data for anomalies, and drafts escalation briefs before they become incidents.

Internal tools & integrations

Connect what does not talk

APIs, CRMs, databases, spreadsheets, portals and legacy applications, joined into one dependable operating workflow, built around your stack, not a pre-built connector.

In every workflow

AI proposes the move. Deterministic code executes it.

Every product wraps its model in a state machine. The model picks the transition; only validated code writes anything down.

  • Structured validation
  • Tool use with guardrails
  • Human-in-the-loop gates

One transition, start to finish

  1. The model proposesone transition, as structured output
  2. Schema checkwrong shape, out of range, not allowed here rejected → back to the model
  3. Human gateon the transitions you mark as gated
  4. Validated code executesthe only step that writes anything down

In every workflow

Deployed inside your perimeter, not ours.

The product runs in your VPC, reading your systems with your permissions. Nothing is copied into a Sentrova-hosted platform to run it. Where a hosted model handles inference, only the minimum content that call needs leaves your environment; storage, retrieval and orchestration stay inside your infrastructure throughout.

  • Deployed in your VPC
  • Permission-aware retrieval
  • Your repository, day one

Your VPC, your permissions

  • Your systems of record
  • Retrieval and permissions
  • Orchestration
  • Storage and logs

Only the content that one call needs

Hosted model, inference only

In every workflow

Every action leaves a trail you can follow back.

Every decision keeps its source documents, prompt version and execution context. The answer to “why did it do that” is a record, not a reconstruction.

  • Traceable decisions
  • Exception queues
  • Audit trails

What one decision keeps

Source documents
every page the answer drew on
Prompt version
the exact text that ran, by version
Execution context
inputs, tools called, what came back
Outcome
what was written, or why it stopped

Pulled up per decision, not reconstructed after the fact

Delivery modes

Five ways to start, chosen by what you already know.

Commercial terms are agreed in writing before any build stage starts.

Workflow X-Ray

Best for: You know work is slow or fragmented but do not know where AI fits. Deliverable: a workflow map, bottleneck analysis, AI opportunity backlog and priority roadmap.

AI-Native Pilot

Best for: You need to prove a specific workflow can work safely before committing further. Deliverable: a working prototype, baseline metrics, evaluation plan and production recommendation.

Production Build

Best for: You have a high-value workflow ready to transform. Deliverable: an integrated, governed system, covering interface, data layer, automations, testing and deployment.

Modernisation Sprint

Best for: You already have a tool or AI pilot that is not delivering. Deliverable: an architecture audit, fixes, reliability controls, evaluation and an upgrade plan.

Embedded AI Engineering

Best for: You need an experienced build partner over time, not a single project. Deliverable: a delivery pod working alongside your product, operations or data team.

See exactly how a build runs, phase by phase

Next

Not sure which mode fits?

Describe your operational bottleneck. Matching it to the right system is our job.

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