Build AI into a defined operational journey rather than adding a generic chat window.
Custom AI built around the system you already operate.
When an off-the-shelf product does not fit, Rennix AI designs and delivers a focused application integrated with your data, identity, workflows and deployment environment.
Custom delivery lifecycle
DesignRequirements, workflow, users and constraints
IntegrateData, identity, systems and model services
OperateTesting, deployment, monitoring and iteration
When custom development is justified
Custom delivery is appropriate when the workflow, integration boundary or governance requirement is specific enough that configuring an existing product would create more complexity.
Connect securely to existing applications, documents, cameras, databases and identity.
Own testing, deployment, monitoring, support and controlled iteration after launch.
A product lifecycle, not a prototype handoff
Delivery includes the non-model work that determines whether an AI application survives real users, failures and changing requirements.
- Validated user workflow and acceptance criteria
- Security, privacy, integration and deployment architecture
- Evaluation data, error states and human escalation
- Monitoring, documentation, support and change ownership
From idea to an operating system
Each phase produces a clear decision or piece of evidence before the next investment is made.
DiscoverConfirm the workflow, users, evidence and constraints.
DesignChoose the architecture, controls and measurable acceptance criteria.
PilotTest with representative data and real operational scenarios.
OperateDeploy with monitoring, ownership, support and a change process.
Frequently asked questions
How is a custom AI project scoped?
Discovery defines the users, workflow, evidence, integrations, constraints and measurable acceptance criteria before implementation.
Can you integrate with existing systems?
Yes. Integration can cover databases, APIs, documents, cameras, identity providers and operational applications, subject to access and technical discovery.
What happens after launch?
The production plan can include monitoring, incident handling, evaluation, model or prompt updates and ongoing product iteration.
Start with a clear operational problem.
We will help you evaluate value, data, risk and the right deployment path before committing to a build.
Book a discovery session