Get the pilot into production
The demo worked. The business still cannot depend on it. DBHQ closes the gap between a promising AI experiment and a reliable system connected to the way the business actually operates.
Why do promising pilots stall?
The model is rarely the whole problem. Production depends on everything around it working under real conditions.
Missing or brittle connections to systems of record
The demo runs on a sample, a manual export or a one-off connector. It cannot yet read from and write back to the systems the business actually uses.
Unclear evaluation and acceptance criteria
The prototype looks promising, but nobody has agreed how quality will be measured or what evidence will make the system safe to depend on.
Security, privacy and audit gaps
Data boundaries, access, traceability and retention were deferred to get the experiment moving, then became production blockers.
Uncontrolled cost or latency
A workflow that is affordable and responsive for a handful of tests can become slow or unpredictable under real demand.
No owner for production operation
The team that proved the idea is not set up to monitor failures, manage change and keep the system useful once people rely on it.
What does production-ready mean?
A dependable system has a clear job, controlled behaviour and an operating shape the business can own.
A measurable outcome
The system is judged against an agreed result, with evaluation and acceptance criteria that make done observable.
Guardrails and appropriate human controls
The system knows what it may do, when a person must decide and how uncertain or unsafe outputs are contained.
Reliable integrations
Data moves through tested connections to the systems of record, with identity, permissions and failure states handled deliberately.
Monitoring, failure handling and cost controls
Quality, latency, spend and operational failures are visible, with limits and recovery paths in place before they become business incidents.
Documentation and operational ownership
The people running the system know how it works, what to watch, who decides and how to change it safely.
How does DBHQ get it there?
The commercial path follows the risk: define the real gap, ship one accepted outcome, then keep ownership only where it adds value.
Blueprint
Identify the production gaps, agree the measurable outcome and define the acceptance criteria and costed delivery plan.
Sprint
Implement the agreed integrations, controls and operating shape, then ship one defined outcome into production.
Ongoing ownership
Keep senior engineering ownership in place where the system needs continued monitoring, tuning and delivery.
Built for production, not the demo
Secure production AI
Deployed production, network-isolated AI coding assistance inside the secure boundary - and wrote the adoption patterns the engineering team uses
AI product, built solo
A complete AI-powered consumer platform - 28,000+ published products across 1,600+ brands, a recommendation engine, real-time price comparison and a mobile app - designed, built and launched by one engineer in months.
Regulated-grade cloud and integration
Enabled multiple COTS vendors to develop and integrate on the platform. Sole cloud architect for the Azure infrastructure behind a UK digital identity platform interoperable with the major consumer identity wallets.
Questions, answered
- Can you work with our existing prototype?
- Yes. I start with the prototype you already have, establish what works and what needs to change, then build from there rather than replacing it by default. Your existing prototype remains yours, and the resulting code and production system are yours too.
- Are you tied to a model or vendor?
- No. The work is model- and vendor-independent. I use the model, platform and deployment pattern that fit your outcome, data and operating constraints, including what you already have where it remains the right choice.
- How is data handled?
- Data handling is designed around your policies and risk. I map what data the system needs, where it can travel, what must stay isolated, who can access it and what must be logged before the production design is agreed.
- What access do you need?
- Enough to understand and test the prototype, its data flows and the systems it must connect to. A Blueprint can begin with read-only access to code, configuration, logs and relevant documentation; any production changes are agreed separately.
- What does it cost?
- The work is scoped and quoted against agreed deliverables, usually as a fixed-fee Blueprint followed by a fixed-price Sprint. The price depends on the production gaps, integrations and controls involved; the scope, price and acceptance criteria are agreed in writing before work starts.
- How long does it take?
- A focused Blueprint defines the gaps and delivery plan first, then one or more Sprints ship the agreed outcome. The time depends on the prototype, integrations and controls involved, so I will not promise a production date until the Blueprint has established the real work.
Make the pilot dependable
Tell me what already works, what is blocking production and where the business needs to depend on it. You will get a straight answer on the path from promising prototype to a running system.
Delivered inside defence, banking and national digital identity
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