AI Applications
Generative and agentic AI applications that work in production.
Discuss your requirementWe design and build AI applications, from knowledge assistants and RAG to agentic workflows, and integrate them with the systems, security and data you already run.
When this helps
- People spend hours searching documents and systems for answers.
- A process has repeatable steps and judgement calls that slow it down.
- A proof of concept works in a demo but not with real users and data.
- You need AI inside existing tools, under your security and identity rules.
How would this work for you?
Answer three quick questions and get a short brief on how we'd approach your ai applications need.
What's included
- Retrieval-augmented generation (RAG) over enterprise knowledge
- Agentic workflows and process automation
- Copilots and assistants for internal teams
- Integration with existing systems and identity
- Guardrails, monitoring and cost controls
- Deployment and support
How we do it
- ShapeDefine the users, the job to be done, what good looks like and what the application must never do.Use case and acceptance criteria
- DesignChoose the architecture, such as retrieval, agents or a trained model, and how it connects to your systems and identity.Solution design
- BuildBuild in short increments and test each one with real users and real data.Working increments
- GuardAdd guardrails, evaluation sets, monitoring and cost controls before go-live.Evaluation results and runbook
- Launch and improveRoll out in stages, measure against the acceptance criteria and keep improving.Production application and support
How we keep quality high
- Answers are grounded in your sources and cite them, so users can check.
- A set of real questions is re-run on every change to catch regressions.
- Agents act only through the permissions you grant, and people approve high-impact steps.
- Usage, cost and failure rates are monitored from day one.
Why Qylis AI
Built for production, not demos
Evaluation, guardrails and monitoring are part of the build, not added afterwards.
Fits what you run
We integrate with your systems, data and identity instead of asking you to move.
Tested by specialists
Our testing and certification team checks applications before they reach users.
Right model for the job
A hosted model, an open model or one we train for you, chosen on cost, privacy and accuracy.
Team profiles, tools, certifications and references are shared directly by our team, matched to your requirement.
Ways to work with us
Proof of value
A working slice on real data, judged against agreed criteria.
Build and launch
Design, build, test and roll out the full application.
Run and improve
Monitoring, support and continuous improvement after launch.
Every engagement follows the same rhythm: understand, assess, scope, deliver, with evidence against agreed criteria at each step.
Questions
What is retrieval-augmented generation (RAG)?
An approach where the application first finds relevant passages in your own documents, then asks the model to answer from them. Answers stay current and users can check the source.
How do you stop an assistant from making things up?
By grounding answers in your sources, re-running a set of real questions on every change, and designing the assistant to say when it does not know.
Can the application run in our cloud?
Yes. We deploy to your cloud or on-premise environment where required.
What does Qylis AI's AI Applications offering cover?
We design and build AI applications, from knowledge assistants and RAG to agentic workflows, and integrate them with the systems, security and data you already run. It includes retrieval-augmented generation (rag) over enterprise knowledge; agentic workflows and process automation; copilots and assistants for internal teams; integration with existing systems and identity; guardrails, monitoring and cost controls; deployment and support.
How does an AI Applications engagement start?
Understand: We start with the business requirement and the outcome you need to measure. Assess: We review the data, systems and constraints, and confirm where AI makes sense. Scope: We agree scope, acceptance criteria and a first deliverable you can judge. Deliver: We deliver in increments, with evidence against the agreed criteria at each step.
How do I discuss an AI Applications requirement with Qylis AI?
Send the requirement through the contact form on this page. A solution lead replies within one business day.
Talk to Qylis AI
Tell us the requirement. A solution lead replies within one business day.
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