Operating layer · v0 launch

Governed AI production, between your strategy and your stack.

Halestone designs, deploys and operates custom AI production systems for organisations that need accountable, governed AI running inside their day-to-day operations — with named owners, acceptance tests, role-based controls and audit-grade provenance from day one.

Start a discoveryRead the approach
4–8 wk
Discovery → production
Named
on-call rota + owner
Audited
request & decision log

The Halestone layer

BUSINESS STRATEGYPriorities, owners, regulated workflowsHALESTONE · GOVERNED OPERATING LAYERDesigned · Deployed · Operated · OwnedAcceptance testsRole-based controlCost & incident loopAudit-grade logEXISTING TECHNOLOGY STACKCRM · ERP · IdP · Data · Internal tooling

Built into your environment. Not a vendor shelf. Not a personal copilot.

Our position

Not a licence. Not a copilot. Not an automation tool.

Operating layer

Halestone sits between what your business is trying to do and the technology it runs on. We are the missing rung, not the platform and not the strategy.

Production-grade from day one

Every system is delivered with acceptance tests, monitoring, cost control and a named owner in place. There is no ‘demo mode’ and no warm-up phase.

Owned, then handed over

We operate the system through cut-over so your team runs it day-to-day from day one. Post-launch stewardship is contracted — it never becomes abandonment.

Application territories

Five working territories. One operating posture.

Halestone takes work wherever your team has a workflow that needs to be faster, more accurate, or more consistent — and that already has a regulator or a finance director watching it.

Each territory follows the same delivery lifecycle — what changes is the workflow, the buyer, and the controls environment we wire into.

  1. 01

    Operations

    Production scheduling, logistics, field ops

    Decision support, document intake and routing, exception escalations, and reporting that has to survive a regulator looking at it on a Tuesday morning.

  2. 02

    Revenue & customer delivery

    Sales ops, onboarding, support triage

    Quoting, contract summarisation, intake to delivery, customer signal aggregation — built against your CRM and ordering systems, not bolted on top of them.

  3. 03

    Knowledge & decision support

    Research, advisory, internal search

    Grounded retrieval across the corpus your analysts actually use, with provenance carried end-to-end so the answer is auditable, not just plausible.

  4. 04

    Finance & administration

    Close, controls, compliance workflows

    Workflows that sit inside the controls environment — segregation of duties, evidence retention, and reviewable approvals rather than a black box that signs things.

  5. 05

    Internal product capabilities

    Engineering productivity tooling

    Repo-grounded assistants, migration analysis, incident postmortem drafting — wired through SSO, scoped to repos, and rate-limited against the rest of your tenant.

Delivery lifecycle

From a signed success criterion to a system with a runbook.

Discovery is paid, scoped, and produces a written deliverable. Build ships with the acceptance test suite already inside the repo. Integration is change-controlled; operation is contracted and reviewable.

  1. Phase 01

    Discovery

    Named owners, the actual workflow, the data the system is allowed to touch, and the regulated step it must not skip. We leave with a signed success criterion.

  2. Phase 02

    Build

    A bounded system, instrumented from day one, that you can drive against real tickets before anyone calls it production. Logs, traces, and cost meters live alongside it.

  3. Phase 03

    Integration

    Cut over alongside your existing process, not over the top of it. SSO, role maps, secret handling, and data egress paths follow your environment, not a vendor default.

  4. Phase 04

    Operate

    Weekly operation reviews, monthly cost reconciliation, and a named on-call rotation. Improvements go through change control, not a Friday afternoon commit.

Acceptance tests, run before production

Each system is tested under bounded limits. Handoffs into production are validated, not assumed.

  • Ambiguity tolerance
  • Fallback behaviour
  • Provider failure
  • Prompt-injection resistance
  • Data egress negative tests
  • Regression against the live corpus

Stewardship after launch

The system remains owned after launch, not abandoned to the buyer.

Halestone's ongoing operation is named, scoped, and reviewable. Six things stay in place even when no one is in the room.

Discuss ongoing operation

  • Monitoring

    Latency, error rate, refusal rate and per-tenant cost, with a single dashboard the on-call rotation agrees to watch.

  • Cost control

    Per-feature budgets, monthly reconciliation against forecast, and a kill-switch on the model route if a workload drifts.

  • Incident response

    A named rota, an escalation tree, and a written postmortem within five working days — signed off by a person, not generated.

  • Controlled improvement

    Changes land through change control, with the previous behaviour preserved until the new one has passed the same acceptance set.

  • Audit trail

    Every request, retrieval and decision is recorded with timestamp, identity, source and outcome. Reviewable, not exportable-on-request.

  • Renamed owner

    A specific human at Halestone is accountable for each system, with their name on the runbook — not a shared mailbox.

Procurement & risk

What teams ask before signing.

Common questions from audit, procurement, security and legal. If your question isn't here, the same address works.

Send a vendor-review pack

Next move

If your team has moved past pilots, the next step is a discovery — not another tool.

Discovery is paid, scoped, and produces a written deliverable your procurement team can attach to its vendor review. Expected cycle: four to eight weeks from signed discovery to first production cut-over.

Start a discoveryhalestone-esoadq@polsia.app