Revoleap + OpenAI

Intelligence is the beginning.
Useful is what we build.

We connect OpenAI’s models and tools to the work your people and products need to do. From the first useful workflow to an AI application you can trust, operate and improve.

Build with usExplore the capabilities

For the people turning possibility into everyday work.

Platform possibility.
Revoleap craft.
Give intelligence the right context.

Authorised knowledge, documents and business rules.

01 / What we build

Deep work.
Across the platform.

OpenAI keeps widening what software can do. We focus on the last mile: your context, your systems, your users and a clear standard for what good looks like.

Explore our engineering capabilities.

01AI products & multimodal experiencesTurn model capability into a product people choose to use.

Streaming interfaces, document and image understanding, generated imagery, structured extraction and multimodal workflows. We design clear error paths, tenancy boundaries and human review into the product.

Responses API · Structured outputs · Vision · Image generation
02Agents & business automationDelegate a bounded job with a clear owner.

Select the orchestration model, connect scoped tools and define approval gates. We handle durable state, retries, timeouts and escalation around the business task.

Agents API · Agents SDK · Function calling · MCP
03Enterprise knowledge & researchGive every answer a defensible source.

Permission-aware knowledge access, content ingestion and citation experiences. We test missing evidence, stale content and conflicting sources against representative user questions.

File search · Retrieval · Web search
04Realtime voice & audioCreate a conversation that can complete a task.

Voice interfaces, interruption handling, telephony and authenticated business tools. We design consent, context transfer and a human fallback into the conversation.

Realtime API · WebRTC · SIP · Transcription
05ChatGPT adoption & integrationMake everyday AI useful across the organisation.

Workflow discovery, workspace setup, knowledge and tool integration, team enablement and adoption measurement. Identity and connected-service permissions are agreed with the customer’s administrators.

ChatGPT · Workspace controls · Connected tools
06Codex & engineering enablementHelp engineers build with a stronger feedback loop.

Repository context, reusable instructions, development environments and review gates. We establish a measured rollout around code quality, useful automation and developer ownership.

Codex · Repository workflows · Review & testing
07Model quality & optimisationFind the best fit for the actual work.

Task-specific datasets, regression checks, prompt and model comparisons, and latency or cost tuning. Where supported and justified, we assess fine-tuning against simpler alternatives.

Evaluation · Model selection · Prompt caching
08Production controls & operationsKeep the surrounding system as strong as the model.

Service identity, tenant isolation, rate handling, budgets and observability. We validate the relevant data controls and product entitlements before selecting a deployment approach.

Projects · Access controls · Usage monitoring
02 / Engineering blueprints

See the pieces
work together.

Starting architectures for real business needs. We shape the implementation around your systems, constraints and operating team.

Knowledge to action

An assistant that knows where its authority ends.

For service and operations teams working across documents and business systems.

  1. 01 / AskYour app + authenticated user
  2. 02 / GroundPermission-aware retrieval
  3. 03 / ActResponses + approved functions
  4. 04 / RecordSystem of record + audit trail

Control points

Source-level access checks and approval before consequential writes.

What we leave with you

Retrieval pipelines, tool contracts and an evaluation dataset.

How we validate it

Test source correctness, access boundaries and completed tasks.

AI-native product

Intelligence inside the customer journey.

For product teams turning a model-enabled feature into a dependable service.

  1. 01 / ExperienceStreaming product interface
  2. 02 / ReasonResponses + structured outputs
  3. 03 / IntegrateTenant-scoped product services
  4. 04 / LearnFeedback + regression evaluations

Control points

Tenant separation, output validation and deliberate failure states.

What we leave with you

A production integration, model routing and release checks.

How we validate it

Assess task quality, time to useful response and cost per outcome.

Engineering enablement

A practical adoption path for the people writing the code.

For engineering teams introducing Codex into their existing delivery process.

  1. 01 / PrepareRepository context + environments
  2. 02 / BuildScoped Codex tasks
  3. 03 / ReviewTests + human code review
  4. 04 / MeasureQuality + useful time saved

Control points

Repository permissions, environment boundaries and merge ownership.

What we leave with you

Team instructions, repeatable workflows and adoption guidance.

How we validate it

Compare reviewed changes, regression rates and developer feedback.

03 / Engineering with accountability

Start with one task worth getting right.

Bring a workflow, a sample of the data and a person who owns the outcome. We will work through the model, integration and evaluation choices together.

Explore AI Engineering
01 / Decide

A useful first scope.

The business task, system boundaries and acceptance criteria, agreed together.

02 / Build

Work beside your team.

Visible engineering, reviewed decisions and working increments you can assess.

03 / Transfer

Leave lasting capability.

Code, operating guidance and the knowledge to own what comes next.

Explore the platformOpenAI agent architecture Responses API Workspace controls
Where to start

Let’s start with the work
that matters.

A working conversation about the opportunity, the constraints and a useful first step.

Begin a conversationThe Leap Assessment / 90 minutes