Smart search
Let users search records and content in plain language.
Who it’s for
Who this is for and the problems it solves
Typical clients
- SaaS companies adding AI features to their product roadmap
- Businesses with internal tools that need smarter search or automation
- Product teams without in-house AI engineering capacity
- Companies with older systems they can’t replace but want to extend
Common problems
- Customers expect AI features and your team lacks the time or specialist skills
- Previous experiments never made it from demo to production
- Costs, response times or accuracy are unclear before committing
- Your codebase or infrastructure makes changes risky
Use cases
What we can build
Examples of our capabilities, not descriptions of specific client projects.
Summaries and drafting
Summarise records, conversations or documents inside your app.
Classification and tagging
Sort tickets, leads or documents automatically.
In-app assistants
Help users complete tasks using your product’s data and actions.
Scope
Scope, deliverables and what we need from you
What we deliver
- Review of your architecture, data and constraints
- Feature design and model selection, with cost and response-time estimates
- Integration code, APIs or services that fit your stack
- Evaluation sets and automated tests
- Usage monitoring and cost controls
- Documentation and knowledge transfer to your developers
Data & integration requirements
- Access to the relevant codebase or API documentation
- A test or staging environment
- Sample data representative of real use
- A technical contact on your team
Delivery
How we deliver and evaluate
Discovery
Understand the workflow, the data and what success looks like. Agree scope and measurable targets.
Prototype & evaluate
Test the approach on a sample of your data against agreed criteria before a full build.
Build & integrate
Develop, connect to your systems and test with your team, with regular demos.
Deploy & support
Release to your chosen environment, hand over documentation and agree ongoing support.
We build an evaluation set from your real data, compare model options on accuracy, cost and speed, and ship behind a feature flag or to a pilot group before full release.
Evidence
Relevant work
We don’t yet have a published client case study for this service. We can walk you through relevant work and our approach on a call.
Options
Ownership, deployment and support
Ownership
Ownership of the code, prompts, evaluation sets and any model weights we produce for you is agreed in the statement of work, subject to the licences of any third-party models or components used.
Deployment
Your own cloud account (AWS, Azure or Google Cloud), your on-premises environment, or hosting managed by Kubit’s.
AI models
Hosted models from major providers, open-source models run in your environment, or models fine-tuned on your data, chosen per use case for accuracy, cost and data handling.
Support
Post-launch support and maintenance are agreed per project, including monitoring, updates and response times.
FAQ
Questions about this service
Do you work inside our codebase?
Yes, if you prefer. We can contribute to your repositories under your review process, or build a separate service your software calls.
How do you control AI running costs?
We estimate costs during the prototype, choose models to suit, and add caching, limits and usage monitoring.
Can you work with our developers?
Yes. We often work alongside in-house teams and hand over with documentation and walkthroughs.