AI application integration
Bring a useful AI capability into an existing application or a new platform. We connect the user experience, approved data, provider APIs, and operational controls needed to move beyond a standalone experiment.
THE BUSINESS CONTEXT
A demonstration can show that an AI model performs a task. An application must also handle authentication, permissions, slow responses, failures, costs, updates, and user expectations. Those surrounding decisions determine whether the feature is practical for everyday work.
Plateau’s application approach combines conventional software engineering with AI evaluation. We define the feature around a specific journey, keep important business rules explicit, and give your team a way to understand the result and its limits.
YOUR FIRST ENGAGEMENT
Focused Pilot
Add one AI feature to an existing application in a test environment with permissions, usage limits and a fallback.
Discuss This PilotApplication access, a staging environment, authorised data and an owner for the user journey.
Measures are agreed for your project. Results depend on the data, workflow and evaluation; they are not guaranteed improvements.
WHAT WE DO
AI may be useful inside an existing screen: a summary beside a record, a draft within a service workflow, a search across approved documents, or assistance while preparing a report. We define what the user provides, what the application returns, and which next actions are available. Loading, cancellation, correction, and fallback states are part of the design.
The integration layer manages provider calls and the information supplied to them. We consider document retrieval, structured outputs, validation, and the transformation needed by downstream systems. Secret keys remain outside the browser. Access to business data is checked before it reaches the model, and generated output is treated as information to validate rather than trusted executable instruction.
A production feature needs timeouts, reasonable usage limits, and useful responses when the provider is unavailable. Repeated requests, long inputs, and large output volumes can affect cost and response time. We identify the usage assumptions and the monitoring needed to compare them with reality. Provider or model changes should be evaluated before they reach all users.
AI can help explain or summarise approved business information, while calculations and record retrieval remain grounded in defined data operations. We distinguish computed values from generated commentary and show the basis for important numbers. This is useful for operational summaries and reporting assistance, where a confident narrative should never replace the underlying evidence.
A DEFINED ENGAGEMENT
Your proposal defines the exact scope, responsibilities, milestones, and exclusions. Depending on the engagement, the work can include:
WHERE IT FITS
Add drafting, search, or summarisation to a business tool.
Offer a focused assistant inside an established journey.
Explain approved records with traceable supporting information.
WHO THIS CAN HELP
Explore example workflows and the customer groups these services are designed to support.
A PRACTICAL FIRST STEP
Choose one useful task, agree how the result will be checked, and use the evidence to decide what should happen next.
QUESTIONS, ANSWERED
Often, yes. We first review the application structure, hosting, data access, and the feature you want. The integration may be an isolated service or part of the existing backend, depending on the environment.
Not necessarily. A provider model, a carefully designed workflow, and relevant source retrieval may be enough. The choice follows evaluation against your task. Custom training has additional data and maintenance requirements.
The application can validate structured outputs, show source references, request human review, and offer a fallback. The appropriate controls depend on the task. No model should be assumed to produce correct results every time.
We estimate input volumes and task frequency, then consider limits, caching where appropriate, and monitoring. Provider pricing and terms are confirmed when the implementation is scoped. Operating costs are separate from development work.
A well-defined integration boundary can reduce the amount of application code tied to a provider. Switching still requires checking model behaviour, data handling, cost, and quality against the project’s evaluation cases.
CONNECTED CAPABILITIES
Build the application your operation actually needs.
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Connect AI reasoning with the tools your team uses.
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Help customers and colleagues find information in a natural conversation.
Explore This SpecialtyA CONVERSATION IS A GOOD PLACE TO START