Service lines
Three ways to put AI into production
Independent offers. Take one on its own, or let them compose into build, ship and operate. Below is the comparison, including the row most of this industry leaves out: what each one needs from you.
No line requires another. Managed AI Support applies to systems we did not build.
The three lines compared
- What it is
- A system that decides and acts inside your tools, within a permission boundary.
- Production software built around your workflow, with model capability inside it.
- Ongoing engineering operations for AI systems that are already live.
- When it fits
- Repetitive work that still needs judgement, or work stranded between two systems.
- A workflow that is genuinely yours and currently held together by files and habit.
- Something is deployed and nobody can prove it still works as well as it did.
- What it needs from you
- A way in (an API, a database or an export) and someone who knows the exceptions.
- Access to the people doing the work, and a decision on where data may live.
- A review of the existing system, and agreement on what correct looks like.
- What you have at the end
- The agent, its tools, its evaluation set, and a readable record of every run.
- The application, its source, its architecture docs and runbooks, all yours.
- A versioned evaluation suite, monitoring, and a known-good configuration to return to.
- Can it be bought on its own
- Yes.
- Yes.
- Yes, including for systems we did not build.
AI Agent Development
- What it is
- A system that decides and acts inside your tools, within a permission boundary.
- When it fits
- Repetitive work that still needs judgement, or work stranded between two systems.
- What it needs from you
- A way in (an API, a database or an export) and someone who knows the exceptions.
- What you have at the end
- The agent, its tools, its evaluation set, and a readable record of every run.
- Can it be bought on its own
- Yes.
Custom AI Applications
- What it is
- Production software built around your workflow, with model capability inside it.
- When it fits
- A workflow that is genuinely yours and currently held together by files and habit.
- What it needs from you
- Access to the people doing the work, and a decision on where data may live.
- What you have at the end
- The application, its source, its architecture docs and runbooks, all yours.
- Can it be bought on its own
- Yes.
Managed AI Support
- What it is
- Ongoing engineering operations for AI systems that are already live.
- When it fits
- Something is deployed and nobody can prove it still works as well as it did.
- What it needs from you
- A review of the existing system, and agreement on what correct looks like.
- What you have at the end
- A versioned evaluation suite, monitoring, and a known-good configuration to return to.
- Can it be bought on its own
- Yes, including for systems we did not build.
AI Agent Development
An agent is only useful once it can reach the systems where work happens. Yours gets real tool access, a scoped identity, and behaviour you can measure.
Agents need somewhere to act. If the systems involved have no API, no database access and no export, opening that door is the first piece of work, and you will hear that before you commit to an agent.
AI Agent Development in fullCustom AI Applications
Applications built around your workflow, with AI doing the part of the job it is genuinely better at, and an interface people can use, trust and correct.
Custom software is worth building when the workflow is genuinely yours. If an existing product already does 95 percent of the job, we will say so, and build only the integration that closes the gap.
Custom AI Applications in fullManaged AI Support
AI systems degrade in ways ordinary software does not. Providers change models, prompts drift, data shifts, edge cases accumulate. This is the discipline that keeps a deployed system right.
We can operate a system we did not build, but only after a review that establishes what it does, how it fails, and what correct looks like. Where no evaluation set exists, building one is the first engagement rather than an optional extra.
Managed AI Support in fullHave a workflow AI should be doing?
Bring the real one: the workflow with the exceptions, the four systems, and the person who knows how it actually runs. You will get an honest answer on whether AI belongs in it, and what it would take to build.