A focused product scope
User journeys, interface decisions, integration boundaries, and acceptance criteria before a larger build is committed.
Custom AI software
Custom AI software. Built around the task.
Build an internal tool, customer workflow, or AI feature for the work your current software does not fit. Start with one useful user journey, test the difficult assumptions, and agree what production readiness requires.
Document review screen
A useful handoff
See the source. Make the call.
| Requirement | Proposed finding | Reviewer action |
|---|---|---|
| Delivery contact | Not found in the document | Ask for the missing contact |
| Supplier reference | Source and intake differ | Inspect both references |
| Required attachment | Listed but not included | Request the attachment |
Check findings before export. Keep the source beside the decision.
Built around your work
When this makes senseRecognize
Recognize
the friction?
Spreadsheets and generic tools are useful until the real process lives in the gaps between them. A custom build makes sense when the workflow, interface, or integration is specific enough that adapting another product creates more work than it removes.
A good fit when…
People work around generic tools because the real task needs a different interface or sequence.
A customer or internal team needs to review AI output alongside the source it came from.
You want to add a focused AI feature to an existing product or build a dedicated workspace.
Tangible work
What you take away.
Working software
An agreed application or feature with its useful non-AI workflow intact. AI is a component, not a substitute for product design.
A maintainable handoff
Documentation, deployment requirements, source-code and ownership terms, and a clear discussion of ongoing maintenance.
Put it to workReal tasks.
Real tasks.
A more useful way through.
Find a starting point for your team.
01
A document review workspace
Put the source, requirements, and proposed findings together so reviewers can inspect each decision.
Explore the workflow 02A proposal preparation tool
Guide a commercial team from approved scope and pricing inputs to an editable draft.
Explore the workflow 03A workspace for CRM cleanup
Show suspected duplicates and inconsistent fields together with the evidence needed to resolve them.
Explore the workflowOne possible workflow
From input to a clear next step- 01 / The starting point
A reviewer needs to compare a supplier document with a requirements list.
- 02 / The right context
Bring the source document and approved checklist into one workspace.
- 03 / Prepared for review
Show proposed findings beside the passages they came from.
- 04 / A person decides
A reviewer accepts, edits, or rejects each finding before an export.
From first conversation to handoffA clear start.
A clear start.
An agreed finish.
- 01
Shape the smallest useful version
Walk a user through the task and define the non-negotiable result, not a long feature inventory.
- 02
Prototype the risky parts
Validate the interaction, integration, and AI quality before expanding the scope around uncertain assumptions.
- 03
Build for real operation
Exercise permissions, failure states, accessibility, and recovery. Agree the handoff and launch decision separately.
Agree the scopeAgree the scope
Agree the scope
and the limits.
A custom build is not a universal seven-day delivery. Hosting, third-party licenses, source ownership, maintenance, and support are agreed in writing. Regulated or consequential decisions require additional specialist review.
Security and data questions ↗A few useful answers
Before we begin.
What does a first custom software scope deliver?
A first scope can define the user journey, prototype a risky interaction or integration, and establish the acceptance criteria for a working version. Agree which screens, actions, and system connections are included. A prototype tests a question; production deployment and operations require additional checks.
Can you add an AI feature to an existing application?
An existing application can be the starting point. Review its architecture, user permissions, data access, deployment process, and the product team's responsibilities. The useful scope may be a focused feature inside the current experience, with an explicit fallback when AI output is unavailable or unsuitable.
What determines custom AI software development cost?
The main drivers are user journeys, integration complexity, data preparation, permission requirements, AI evaluation, and production operations. Hosting, model usage, and third-party licenses are separate operating costs. Agree deliverables and assumptions before pricing, including how changes to the scope will be handled.
What affects the delivery schedule?
The schedule depends on unresolved product decisions, integration access, source quality, and the review needed for launch. Testing the uncertain parts first helps establish the remaining work. Agree milestones around working behavior and acceptance evidence, with client dependencies identified alongside development tasks.
Who owns the code and data?
Source-code ownership, licensing, access to repositories, and data-handling terms must be agreed in the contract before work starts. Third-party components can carry separate licenses and usage terms. The handoff should identify what is delivered and what is needed to operate or change it.
What happens after the software is handed over?
Agree who deploys updates, monitors failures, manages credentials, and handles user questions. The handoff can include operating documentation and deployment requirements. Ongoing development, maintenance, and support need an explicit scope, including how urgent issues and changes to external services will be handled.