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Tanooki Labs

AI STRATEGY

Put AI to work on something that matters.

Bring us a process that takes too much time or a product idea you want to test. We’ll work out where AI could help, test it with your data, and build on what proves useful.

Talk about your project

Find a useful place to start.

Start with the work itself. Where does time go? What information is available? What happens when something goes wrong?

A specific opportunity

A workflow and a clear reason to improve it.

A working experiment

Something you can try with representative examples from your work.

Evidence for the decision

Results, failure cases, and a view of the effort involved.

A practical next step

Improve the experiment, integrate it, or choose a different approach.

Test it on the work you actually do.

A convincing demo is a starting point. We work through everyday cases and difficult ones so you can judge whether the result is useful.

  1. Choose representative examples

    Include the common tasks and the cases that are easy to get wrong.

  2. Agree on useful results

    Define what good looks like and where a person needs to decide.

  3. Compare and improve

    Review the output, investigate failures, and refine the approach.

  4. Plan for everyday use

    Connect it to the workflow, with monitoring and clear ownership.

Keep the decision grounded in evidence.

  1. Real examples
  2. Expected result
  3. Observed result
  4. Next decision

BRIGHTLINES

AI that fits into the analyst’s work.

Brightlines’ Verdict AI combines rules and an LLM to categorize search results and process data-broker findings, with analysts in the loop. At Leap Fund, our work also includes guidebook retrieval and plain-language access to program data.

Read the Brightlines story →

Bring us one process.

You don’t need a finished AI strategy. A specific task and a few examples give us a useful place to begin.

The work

Show us the task that takes too long or holds up the team.

The examples

Bring the inputs, the current output, and what a better result would look like.

The constraints

Tell us who uses the result, what data is involved, and which mistakes matter.

We build with AI every day. AllSpark is one of the tools we use to put that experience into practice.

Explore our work →

Which part of the work takes too long?

Bring a workflow or a product question. We’ll talk through whether AI could help and what it would take to find out.