Production agents, secure MCP connectors and AI applications for UK and US organisations. Built around real workflows, governed actions and measurable outcomes. You own the code.
MCP tools live
Audited MCP tool calls
AI language apps shipped
Code ownership at launch
Value appears when AI connects safely to data, tools, decisions and operating teams. We build the complete production system around that connection.
Turn a defined workflow into an agent that can reason, call approved tools and return structured results. High-impact actions stay permissioned, logged and reviewable.
Connect ChatGPT-compatible clients to your real systems through OAuth-secured MCP services, explicit tool boundaries and auditable activity.
Ship AI as a complete web or mobile product, not a demo: authentication, subscriptions, contextual memory, usage controls, monitoring and ongoing iteration included.
Define success before launch, test important failure modes and add proportionate privacy, grounding, escalation and observability controls around the model.
Every stage produces something reviewable: an outcome definition, a control design, a working system and production evidence.
Map the workflow, users, data boundaries and measurable business result. Select the smallest production-worthy use case, not the flashiest demo.
Define tools, permissions, grounding, model behaviour, human approval points, evaluation criteria and the operational evidence needed after launch.
Implement the application and integrations with server-side credentials, authenticated access, structured outputs, usage controls and observable failure states.
Release gradually, exercise the real workflow, measure quality, latency, cost and outcomes, and keep an auditable record of what changed and why.
LogicLeap already operates the integration and product foundations needed for serious OpenAI delivery. We report exactly what the evidence proves.
A production portal integration exposing 29 controlled tools and 127 audited tool calls. It is ChatGPT-compatible; current telemetry does not claim ChatGPT-specific adoption.
A shared architecture supporting 21 publicly listed language apps, with authenticated access, memory boundaries, metering and account deletion.
Consent, grounding, crisis routing, usage limits, row-level isolation and monitoring implemented across relevant production products.
LogicLeap has been invited to apply to the OpenAI Partner Network and is completing the technical assessment. We do not claim approved partner status or display a partner badge before confirmation.
View the portal case studyLogicLeap has been invited to apply to the OpenAI Partner Network and is completing the technical assessment. We do not describe ourselves as an approved OpenAI Partner or display a partner badge unless and until OpenAI confirms that status.
No. We select a provider against the task, data, quality, latency, cost and operational requirements. That experience makes our OpenAI recommendations more credible: we use OpenAI where it is the right production choice, not simply because it is available.
A production system must authenticate users, connect to controlled tools and data, handle failure, record usage, protect sensitive actions and produce evidence of quality and value. The model is one part of that system.
Yes, where the client and account support the required connector route. We build OAuth-secured MCP services with explicit tools, redirect validation, audit logging and operational controls, then validate the real authorisation and tool-use flow.
A focused discovery and architecture engagement can begin within days. A scoped first production workflow is typically designed, built and validated in four to eight weeks, depending on system access, data sensitivity and approval requirements.