Which ad spend is bringing us customers—and what should we test next?
Follow spend through to outcomes, agree on the next experiment, and give Callie the authority to make the change and check its results.
CalliopeatWork
How work feels today
Stuff everywhere.
Answers nowhere.
Somewhere along the way, getting a number became a department. Reports that need other reports. Questions that wait in someone’s inbox.
at Work
Business, in motion With Callie
Understands your business.Carries the work through.
Meet Callie, an AI colleague who learns how your business works. She connects the facts, investigates what needs attention, and carries out the work you entrust to her. Each conversation can become a better way of running the business.
The foundation underneath
Better context. Better decisions.
Useful decisions need facts you can trust. Callie brings information together, investigates records that disagree, and can collect what’s missing. She works from maintained copies in her own workspace, keeping analysis traffic off your operational systems. That foundation supports the decisions and work that follow.
The work, on screen
See her work.
Follow a real investigation into the data it builds, the work it keeps running, and what becomes possible next.
How she got there · 6 beats
The next question starts further ahead.
We had advertising results, but couldn’t connect enough of them to the campaigns and settings behind them. The conversation changes the data available, the work that repeats, and what can be answered next.
The gap
The numbers weren’t enough.
The TikTok summary held spend, but most rows couldn’t be connected to the current campaigns and ad groups. Adding a directory of names wouldn’t explain which campaigns produced those results.
The campaign directory is useful. The spend still needs a reliable connection. The second look
Some of the answer was already here.
The follow-up asks whether more detailed source tables already exist. Callie looks again and corrects herself: they do. The reporting model was using the less detailed feed. She connects the campaign and ad-group results it had been leaving out.
The source checks stay in the trail as the work moves into enrichment. The broader picture
Bring the missing context in.
The request expands to Google and Meta. Callie brings in campaign settings and status, then adds them to the shared reporting data. She checks that the added detail preserves the existing columns and doesn’t multiply the spend totals.
More context for the same results, with the totals checked against their sources. The ongoing work
Keep it coming.
The enrichment becomes a managed job set to run every twelve hours, calling the connected ad tools through MCP from SQL in Callie’s own database. The collector completes a verified run; the schedule, stored results, and run history stay together.
A successful run, a schedule, and the tables it maintains—all in view. The next question
Start remembering what changes.
Today’s campaign settings don’t tell you what was configured last month. The user raises that limitation. Callie adds a historical capture after each successful enrichment, so future investigations can compare the settings observed over time. That history starts here.
History capture joins the same recurring job, after enrichment succeeds. The history table stays linked to the job that maintains it. The thing you can use
Now put it to work.
The expanded data becomes a working cross-platform view. A follow-up brings Salesforce leads and cost per lead into the headline comparison, while campaign-level attribution stays limited to what the data supports. The screen is one result. The next investigation gets the rest.
The snapshot and first live version, beside the build conversation. The working view is already prompting the next question.
The next question starts further ahead.
Your definitions, decisions, evidence, and useful methods stay available after the conversation. A question can lead to a working tool; a useful check can become a standing assignment. As your team works with Callie, you build an operating memory of how the business gets things done.
The everyday work
Between assignments.
You didn’t have to ask.
She notices work worth doing. Let her investigate while you’re elsewhere, then come back to findings and a plan.
The Floor
She works. You can see where things stand.
The Floor keeps what’s underway, what needs you, and what’s finished in view.
The Gallery
The work stays within reach.
The Gallery keeps published work and its sources together, from working views and metrics to scheduled jobs.
Everyday questions. Room to follow through.
Examples of where a conversation can lead. There’s no assignment to choose before you join.
Revenue is growing. Why isn’t the margin?
Trace the gap across products, customers, discounts, and delivery costs. Prepare the follow-up, then keep checking whether the situation improves.
Where are we losing customers, and which losses could we prevent?
Investigate the accounts, prepare relevant outreach for review, and carry the customer’s reply into the next piece of work.
Bring the team.
Unlimited users and specialists. No per-user or per-specialist fees. Capacity scales with the work you need done.
Callie can create specialists for different parts of your business—sales, leads, operations—each with its own memory and working history.
Advanced AI, included in the service.
Advanced AI is included in the service. American frontier models from OpenAI and SpaceX. We select and operate the models behind Callie. No separate AI subscriptions or extra AI bills to manage.
What really is this?
Understanding that leads to action.
Callie connects what your business knows to what needs doing. She can investigate a question, build the tools the work needs, and carry out a standing assignment. You set her authority and can follow the evidence from question to result.
- 01
She follows the work through
Calliope delegates real work to specialist agents — an analyst, a skeptic, a builder — and reviews what comes back before you see it.
- 02
She remembers your business
What she learns working with one person can help the next. People, decisions, definitions, and business context carry forward across assignments.
- 03
Playable SOPs
When she does something well, keep the method. Your team can run it again, ask her to revise it, or put it on a schedule.
- 04
Your data stays yours
One dedicated appliance per company. Your data lives in one place, pools with no one's, and never trains anyone's AI. Full stop.
- 05
Every answer shows its work
You can follow an answer back to its sources and inspect the work behind it.
- 06
You give her the authority
She works within the authority you give her. She asks before going beyond it.
- 07
Guardrails that are code, not vibes
The safety-critical parts are ordinary software with hard rules. The AI works inside the guardrails — never instead of them.
- 08
Works with what you already have
She plugs into the tools you already use — your databases, Google, your ticketing. Nothing gets ripped out. And the tools that only have a screen? Show her once.
- 09
She works while you sleep
Standing jobs watch your numbers overnight, and a personal brief is waiting every morning. If something needs you, it's at the top of the board.
- 10
She makes real things, in your brand
A page for a client meeting, a plan, a project tracked across systems. She builds what the work needs, in your brand. Keep it while it’s useful; the understanding carries forward.
- 11
The work has a ledger
See what your team asked for and received, with a deliberately conservative estimate of the equivalent human effort.