GBCORP BLOG · AI
AI Platform Development: One Layer Under Every AI Step
After the third AI project, a company notices that each one rebuilt the same plumbing: model access, logging, evaluation, cost control. An AI platform builds that layer once, and every later AI step uses it.
AI platform development builds the shared layer that every AI use case in a company runs on: controlled access to models, a record of prompts and versions, evaluation sets that test each step weekly, logs of what was asked and answered, permissions on what data each step may read, and limits on cost. Without it, each AI project rebuilds these parts differently, and nobody can say what the company’s AI is doing or costing. GBCORP builds the platform alongside the first AI step, so it is shaped by real work rather than designed in a vacuum.
What the platform layer holds
| Part | What it does | Why it matters |
|---|---|---|
| Model access | One controlled route to the models the company approves | Swap or add a model without changing every step |
| Prompt and version records | Which instructions each step uses, and when they changed | Every answer traceable to a version |
| Evaluation sets | Real examples with correct answers, run every week | Quality measured, not assumed |
| Logs | What was asked, what was answered, what a person changed | Review and audit |
| Permissions | Which data each step may read | Sensitive data stays where it belongs |
| Cost limits | Spend per step and per month, with alerts | No surprise bills |
Built with the first step, not before it
A platform designed before any AI step exists guesses at requirements and usually guesses wrong. GBCORP scopes the first step, such as extracting data from invoices or answering staff questions from policy documents, and builds the platform parts that step needs. The second step reuses them and adds what it needs. By the third step, the platform is real, tested and paid for by work that already delivers value.
Governance on one page per step
Each AI step gets a page: what it does, what data it reads, who reviews its output, its accuracy and cost this week, and who decides whether it expands or stops. The platform produces the figures automatically. A board or a regulator reads five pages and understands the company’s AI.
Checklist before building an AI platform
- List the AI steps running or planned, and who owns each.
- Choose the first step by value and by how easily it is measured.
- Collect a hundred real examples with correct answers for it.
- Name the data the step may read, and the data it may not.
- Set a monthly cost limit.
- Decide who reads the weekly evaluation report.
The numbers to expect
Scoping in one week, priced on its own. The first AI step with its platform parts in three to six weeks. Later steps as releases at fixed prices, faster because the platform exists. Running costs reported monthly. Customised or more complex functionality is quoted separately before any work starts.
A worked example
Consider an insurance broker whose first AI step reads policy documents and answers staff questions with citations. The step needs model access, a version record for its instructions, an evaluation set of one hundred questions, logs and a cost limit, so those parts are built with it. Three months later the second step, extracting data from claim forms, reuses all five parts and adds only document handling. It goes live in half the time of the first, and both steps appear in one weekly report.
Cost control as a design feature
AI costs scale with use and surprise companies that did not plan for them. The platform tracks cost per step, per task and per month, routes simple tasks to cheaper models, caches repeated answers and stops a step that exceeds its limit until someone approves more. Finance sees AI spend the way it sees any other running cost.
Changing models safely
Models improve and prices change. When a new model appears, the platform runs each step’s evaluation set against it before anything changes in production. If accuracy holds and cost falls, the step moves; if not, it stays. Model changes become a measured decision rather than a gamble.
Permissions on data
Each AI step is given access only to the data it needs, defined in the platform and enforced on every call. Personal and confidential data is masked where the step does not need it. The permissions are listed on the step’s governance page.
People in the loop
Every step has a review rule: what a person checks, when, and how corrections are recorded. Corrections feed the evaluation set, so the measure of quality improves with use. Review is reduced only on the evidence of the weekly figures.
Ownership terms
Platform code, evaluation sets, instructions and logs in the client’s accounts. Model provider contracts in the client’s name where the client prefers. Running costs paid directly by the client, with no mark-up.
Who runs the platform
Under the support plan GBCORP runs the platform: monitoring, model updates, evaluation runs and the weekly report. A company with its own team can take over any part, with documentation and a hand-over period, because the platform sits in the company’s own accounts from the first day.
Questions we hear first
Do we need a platform for one AI project?
No. The first step builds only the parts it needs; the platform grows when the second step arrives.
Are we tied to one model provider?
No. The model-access layer exists so that a provider can be swapped or added.
Does our data train someone else’s model?
Model access is configured with providers’ business terms, and the permissions layer limits what is sent.
Who can see the logs?
Roles you define; logs sit in your own cloud account.
Where to start
The GBCORP AI Development and Automation product is the priced starting point; the GBCORP AI development hub sets out the method. For governance at group scale, read enterprise AI solutions, governance first.
GBCORP operates across 17 countries on 4 continents through six pillars: AI & IT, Innovation, Sustainability, Infrastructure, Premium Business, and EV's & Solutions.
