The Bithart approach

Architecture before automation. Accountability after launch.

A deliberate path from a worthwhile problem to a working system, with decisions, responsibilities and evidence at each stage.

Start with an Architecture Sprint

What evidence do we need before taking the next step?

We work through decision gates rather than assuming every idea belongs in production. The first gate is whether the workflow is worth changing. The next is whether the information, integrations and controls can support it. A successful demonstration is an input to that decision, not the decision itself.

WHAT YOU RECEIVE

At each gate: a written decision, its supporting evidence, open assumptions and named owners for the next stage.

01

Discover the workflow

Observe representative work and identify the cost of today’s hand-offs. Agree a business owner, the scope of a first release and the evidence that would make it worthwhile.

02

Architect the boundaries

Map data, models, software, integrations and human decisions. Decide what the system may do, what it must ask about and how it fails safely.

03

Build and evaluate together

Develop against real examples and review the workflow with its users. Test incomplete information, unsupported requests, connection failures and changed permissions—not only ideal inputs.

04

Release with a responsible owner

Agree operating responsibilities, monitoring and a rollback path. Add use cases only when the first workflow is understood well enough to support them.

  • ✓A decision-ready discovery output
  • ✓Explicit approval and stop conditions
  • ✓Representative acceptance tests
  • ✓An agreed support and improvement model

From a business problem to a working system.

A clear deliverable at every decision.

  1. 01

    Discover

    A mapped workflow and worthwhile problem.

  2. 02

    Architect

    A blueprint, scope and acceptance criteria.

  3. 03

    Build

    Working software tested on representative tasks.

  4. 04

    Deploy

    A controlled release, training and handover.

  5. 05

    Improve

    Quality reviews, maintenance and agreed next steps.

A little more clarity.

A few questions worth asking before you build.

Talk through your project
What happens if discovery shows AI is not the right answer?

The recommendation should say so. A simpler integration, better search or conventional automation may solve the problem more reliably. Discovery is valuable when it prevents an unsuitable build.

Who from our team needs to be involved?

At minimum, the workflow owner and somebody who understands the current systems. Security, legal, data and operational colleagues join where the consequences and dependencies require their input.

What should AI do
for your business?

Tell us what you want to build, connect or improve.
We’ll help define the architecture, the delivery and what it takes to run it.

Bitsy answers from the heart — try one

AI replies via Anthropic. Privacy