Design tenets
- Six commitments set before any code, agreed with Embassy and applied as constraints on every decision that followed.
A conversational surface for the whole enterprise. Reckonsys is engineering Org GPT as Embassy's system of intelligence: one permission-aware interface where employees ask questions of the company's knowledge estate and complete real workflows, on every device they already use.
Embassy runs on systems of record: SharePoint for documents, HRMS for people, SAP for finance, plus payroll, travel and expense platforms. Each holds what an employee needs. None of them answer a question.
Org GPT sits alongside those systems and exposes them through a single conversation. An employee asks in plain language; the platform retrieves what they are entitled to see, calls the right business system, and completes the transaction. It runs on the web, on a Windows desktop client, on native iOS, as an installable PWA and inside Microsoft Teams, from one backend and one design system.
Reckonsys is engineering the platform end to end: architecture, build, hardening and release across all five surfaces.
Org GPT does not bet the platform on a single model, and that was a deliberate architectural position rather than a hedge. Embassy needs to route different workloads to different models, and to change that routing as models improve, without rewriting the application. So the LLM plane sits behind a provider abstraction with unified token accounting, cost controls and fall-over. Claude is a first-class provider within it.
Where Claude earns its place is the work that carries consequences. Grounded answers over Embassy's document estate have to stay inside retrieved material and cite it, because a confident but unsourced answer about a leave policy or an approval threshold will be believed and acted on. Agent routing has to classify intent reliably enough that a payroll question never lands in the travel agent. Both are instruction-following problems under constraint rather than raw generation problems, and both are where Claude's consistency does the most work.
The provider abstraction also makes that claim testable rather than asserted. A dedicated evaluation harness re-runs a curated prompt set on every model change and blocks a merge on regression, so provider selection per workload is settled by measurement.
The programme is structured so Embassy makes its second investment decision on working software rather than a slide. Two commercially independent phases, each sized and accepted on its own.
Delivery runs as dual-track agile: a discovery and design track one sprint ahead of build, and a build track shipping behind feature flags with a demo every two weeks. Trunk-based development, mandatory review, infrastructure as code for every environment, and an LLM eval pipeline that blocks merges on regression.
The outcomes the programme is being measured against.
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