One expensive problem, scoped and fixed.
One costly problem, scoped properly and fixed.
- Typical scope
- One problem, defined in writing
- Starts with
- A paid discovery, if scope is unclear
- Built around
- How you already operate
What you get.
Scoped to one real problem
Built around how you already run
AI where it earns its place
Boundaries on what it may decide
A monitor watching the system
Documentation and a way out
How it gets built.
- 01
Define the problem precisely
- 02
Decide what should not be automated
- 03
Design the system and the failure modes
- 04
Build against real data
- 05
Deploy, monitor, adjust
What is included.
If the problem is not yet clear enough to scope, we will propose a paid discovery rather than a fixed quote on a guess. And a discovery that concludes you should not build this is a valid outcome we will tell you about.
- A written problem definition, agreed before build
- An explicit list of what stays with a person
- System architecture and data flow, documented
- Integration with your existing tools
- Defined boundaries on autonomous action
- Failure handling and a defined safe state
Questions about something specific.
If the problem matches one of the five other services, it is not: a defined service is cheaper and faster. Custom is for the case where the work is specific to your operation and no off-the-shelf shape fits it.
Mapping the process as it really runs, quantifying where time actually goes, deciding what should and should not be automated, and producing a design document with a fixed quote attached. It is paid, and the document is yours whether or not you build with us.
Only where you have said in writing it may. Most systems we build propose rather than decide on anything consequential, with a person approving. Autonomy is granted deliberately, a step at a time.
Every build runs in parallel with the existing process before anything is switched off, so 'it did not work' means going back to how it ran before rather than a business-stopping event.
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