We build AI systems that connect your tools, workflows and knowledge. Start with one useful pilot. Keep control as it grows.
Your servers, cloud account or data centre. Our managed cloud is optional.
Selected work
Public examples. Real interfaces.
A clear place to start.
Watch the original walkthroughWebsite building / public walkthrough
A public walkthrough of the first page, with the steps you can follow.
Watch the walkthroughInside the walkthrough
GemCapture / pilot
Website capture and reconstruction pilot. Preview the concept and request demo access.
Explore the pilot
Capy Boba Club / web and Android
A playful web and Android project, with a public browser version to explore.
Open Capy Boba ClubChoose the work that gets stuck. We map it, build a focused pilot, then help you operate it.
Your server. Connected tools. Clear controls.
Keep facts, decisions and useful context connected.
Move work between people and tools with fewer handoffs.
Connect APIs, agent tools and the interfaces your team needs.
Find the right problem.
Define the scope and success check.
Set up a focused pilot.
Connect your tools and verify the result.
Run it, review it.
Improve what the evidence supports.
Your infrastructure. Your choice.
Yes. We can scope improvements on your servers, in your cloud account or in your data centre. Our managed cloud is optional.
Start with one example: what triggers it, which API receives which fields, and where the result is stored. Then identify who owns a failed run and how it should recover. That gives us a concrete change to scope before choosing a deployment.
Keep your infrastructure and choose a compatible AI provider. Sell.Systems provides AI integration and workflow automation. We can work in your cloud account, on your servers or in your data centre.
Sell.Systems hosting is optional. We can assess local or open-weight models against hardware capacity, licence terms, required features and quality needs. Provider features differ, so switching may require rework and extra cost.
Starter support covers one system and up to 15 approved delivery hours per month. We agree the work, support hours and response arrangements before starting.
For a defined fix, integration change or deployment task. We agree the scope and acceptance checks before work begins.
Setup or migration, hosting, API and model usage, licences and extra hours are quoted and agreed separately. We also agree access, backups and exclusions before work.
Trace one workflow before choosing a platformMemory informs the next step. Rules bound the action. People stay in control.
How useful memory worksIllustrative system diagram
Verified facts, sources and decisions give the next task a better starting point.
Select a layer to explore it. Important actions can require human approval.
Insights
One person. One useful task. A result they can inspect and a workflow they can recover.
Read the guideA useful AI result needs a recoverable request, not only a good prompt.
Read the guideKeep the right context, know where it came from, and update it when the facts change.
Read the guideSeparate control over your workspace from the choice of model that powers it.
Read the guideStart with a repeated handoff you can observe, improve and measure.
Read the guideYes, your existing infrastructure can be the starting point. Trace one task from trigger to stored result, then agree scope, costs and recovery responsibilities. Managed cloud remains optional.
Read the guideYes. We first check the tools, access and APIs you already have. Then we agree on what can be connected safely. A working tool does not need replacing just because we are adding AI.
Yes. We can start with one workflow, integration or prototype. We agree on its scope, price and success check before building. The free 15-minute intro helps us find that starting point; implementation is a separate paid service.
You can review the result, keep the agreed deliverables and decide what comes next. Ongoing operation, maintenance and further development are available as a separate agreed service.
Where the requirements fit, yes. The application, memory and integrations can run on your server. Models may still use an external API or an eligible CLI subscription, so we make those data and cost boundaries explicit.
A backend on your server can still send data to an external model API. We map which fields leave your environment and where they go. If certain data must stay on premises, we can assess local inference after checking your requirements and available capacity.
No. We work within your agreed project scope. A backend on your infrastructure can still send data to external model APIs; we clarify which data goes where. We agree deliverables and which code, configuration and documentation to hand over. Handover does not automatically transfer ownership of unrelated platform code.
Bring one workflow, one idea or one system that needs attention.
15 minutes via Google Meet. No charge. No obligation.