An AI analyst for your company's data

Managers

Which of my campaigns are doing badly this quarter?
Leads per campaign per month this year, by manager.
Tell me everything about this client.One question, every linked record.

Sales

Where should this client open a new office?Joins public US Census income data with where the client already ranks.
How many reviews does this client need to show up on Google Maps, and how long will that take?

Finance

Who owes us money?
Payments by client this year, largest first.Only for roles that see payments in the app.

Operations

What needs attention today?Test phones left on, missing forwarding numbers, sites that are down, ended subscriptions.
What does a caller hear on each of our numbers?

Customer service

Yesterday's voicemails across all my campaigns.
Which reviews have no reply yet, newest first?

Everyone

How many hours did my team log last week?Managers see their team. Everyone else sees themselves.
Give me all of it as a file.Large results arrive as a file and are analysed on your computer.

Ask in English or any other language. The answer comes back in the same one.

Speed and cost

Your laptops do the heavy lifting. The work runs on computers you already pay for. The server part is one thin service in your cloud.

Already paid for

Your team's computers

Claude Code does the thinking
Charts and file analysis run locally
Uses the Claude plans you already have

One thin service

Your cloud

Inside or next to your backend, on AWS or any provider
Checks each person's key
Keeps no copy of your data

Unchanged

Your systems

Their own access checks decide every answer
Read only
Every request logged

You don't pay forNew virtual machinesGPU serversA copy of your data in a warehouseAnother BI licence

What you do need: a paid Claude plan with Claude Code for each person who asks.

Tokens

Spend compute, not tokens. Big data never goes through the chat.

Tokens are what AI usage is measured in, whether you pay per token or work within a plan’s limits. So SearchTrophy keeps bulk data away from the model. Claude writes a short script, your laptop runs it, and only the answer goes back through the chat.

Totals and rankings are computed on the server, not by reading rows in the chat
“Give me all of it” becomes a compressed file, analysed on the laptop with Python or DuckDB
About 45% lower cost on the same 27 real questions after one round of new tools

Claude CodeExample · made-up data

Take every lead this year and find the best weekday for each campaign.

export_leads · 2026 · 48,213 rows → leads_2026.csv.gz duckdb · ran on this laptop

SELECT campaign, dayname(created) AS day, count(*) AS leads
FROM 'leads_2026.csv.gz'
GROUP BY campaign, day
QUALIFY row_number() OVER (
  PARTITION BY campaign ORDER BY leads DESC) = 1;

48,213 rows stayed on your laptop. Only these came back:

Campaign	Best day	Leads
ACME-01 Acme Co.	Tuesday	1,284
SMPL-03 Sample Dental	Monday	962
DEMO-04 Demo Law Group	Thursday	517

One question, before and after

“Which campaigns use the AI receptionist?” A tool shaped like the question replaced dozens of generic lookups.

BeforeAfter

Before93 steps, ~38,000 requests, timed out

After3 steps, 12 seconds

27 real staff questions, before and after one round of new tools

Each row is scaled to its own “before” value. Same questions, run through Claude Code both times.

BeforeAfter

Tool calls646 → 300

Calls spent searching around208 → 106

Refusals17 → 5

~45%lower cost

~20%faster

Later rounds took typical questions from 10–12 steps to 3.

Light pages, too.The ten SaaS homepages we measured on October 25, 2026 transferred between 0.2 and 8 MB each. This page: under 100 KB.

Usage insights

Gets better the more you use it. Slow questions show what to build next.

Someone asks a question.
The question and each step are logged.
Slow questions stand out in usage insights.
A new tool is built, with its instructions in the same release.
Every laptop picks it up at its next start, without anyone noticing.

Tell your team their questions are kept. It's how the tool learns what to build next.

Usage insights · this weekExample data

214questions

3median steps

9refused, outside role

Most asked	Times
Leads per campaign this month	38
Yesterday's voicemails	27
Who owes us money?	11

Slowest	Steps
Which numbers forward nowhere?	11	Build a tool

Get started

Bring three questions your team asks every week.

On a call, we'll show how they would be answered on your systems, and what the build would take.

Book a call

Ask what you’d ask an analyst.