A surprising amount of the evidence is already public.
You don't have to start from scratch. We start with what's already knowable: public filings, regulatory records, and market data. This bond is the first proof case.
Your data makes it specific. The method makes it repeatable.
Then we layer in your internal context: contracts, positions, policies, and invoices. You're left with an answer you can explain and repeat.
Same method when the decision is spend.
The bond is the first proof case. The same work holds for a vendor increase, a contract, or a policy.
Procurement
Should we accept this vendor increase?
Compare the contract, market prices, past pricing, public alternatives, and your own purchase data. Then show what the vendor uniquely provides and what you could replace.
Keep it. Renegotiate it. Knock it out.
How we work
Command. Reveal. Run. Keep.
Bring the question that matters. See what the evidence really supports. Turn it into a repeatable workflow. Own the process long after we're gone.
01 / Command
Start with what matters.
Pick the number someone has to defend: a holding, a filing change, a vendor increase, a policy fail.
02 / Reveal
Show the evidence.
Bring the sources together and make clear what is known and what is still missing.
03 / Run
Run the workflow.
Turn the evidence into a report, monitor, review flow, or other working process.
04 / Keep
Keep what we build.
The data work, rules, workflow, and documentation stay with your team.
“Can I just ask Claude?”
Yes. We do too. The problem is knowing what to trust when a model sounds confident.
We connect the model to the right evidence, checks, and workflow so your team can use it in a real decision and run the same process again.
Two examples built on real data, with the sources visible.
Source check
Ask a question, then check the sources.
Loom uses public data to respond to questions. Each response shows the source, what changed, and the date the data was true. Ask for evidence and you can open the full source trail.
An agent built this signal from public data in days. It combines energy prices, producer prices, and industry use to show when an increase may hold. A team's contract data makes it more precise.