For AI consultants and MSPs

Prove client AI is worth the retainer.

One cockpit above ChatGPT, Zapier, Make, and n8n - owners, costs, approval gates, and a white-label monthly report.

Request a design-partner slot

1,240 runs / mo43 hrs saved$410 stack costsample month

Early-access research - in development

Verdict - support-triage-botSample

RETRAINnot kill

Drift priced monthly

$6,214 /mo at risk

Resolution rate: 92.4% → 78.6%
Window: 11 days
Root cause: Provider swapped the model
Tool-calling: Intact - degradation is local

Method: baseline from your logs x 0.7 uncertainty discount, rework hours at your blended rate. Every number reproducible from the trail.

ChatGPTZapierMaken8nClaudeHubSpotSlackGoogle SheetsStripe

Works from a sanitized export - no access to client systems, accounts or credentials

The verdict

Keep, retrain, or kill - decided on evidence.

When an agent starts failing, the question is never the graph. It is what to do before the client notices. The cockpit answers with a number attached.

KEEP

Metrics hold or improve. The agent keeps running - and the report proves it earned its keep.

RETRAIN

Degradation is local and recoverable: a swapped model, a drifted prompt. Fix it, do not lose the automation.

KILL

Cost exceeds value and the trend will not turn. Stop it on evidence, not on a bad week.

Inside the cockpit

A quiet control layer above the tools your clients already use.

Workflow registry: Every AI workflow has an owner, a tool, a purpose, and a review point.
ROI math: Hours, rates, assumptions, and tool spend in one ledger - weak savings become visible.
Governance-lite: Approval gates, data rules, and incident notes without enterprise GRC weight.
Client report: A white-label monthly report that gives the client a reason to renew the retainer.

Pre-flight, every month

Turn scattered AI activity into a report clients can read.

The loop is the product: four steps a month, and the renewal conversation stops being about whether it worked.

01
Map client workflows
Inventory what runs where: tools, prompts, triggers, data touched.
02
Attach owners and spend
Every workflow gets a human owner, a tool cost, and a time baseline.
03
Review approval points
Mark where a person must sign off before AI output ships.
04
Ship the client-facing report
White-label summary: what ran, what it saved, what needs attention.

Validation intake

Bring one messy client workflow map. Leave with a sharper reporting system.

Early access is interview-led for AI consultants and MSPs who already manage automations for SMB clients.

Validation intake is temporarily unavailable while the private form and booking settings are being verified.

Privacy contract

Tally stores your email and optional consulting answers for early-access research. Cal.com and the connected calendar store booking details. Do not submit client data, payment data, or workflow exports. Records are deleted within 90 days or earlier on request. We do not sell your data.

A quiet control layer above the tools your clients already use.

Workflow registry

Every AI workflow has an owner, a tool, a purpose, and a review point.

ROI math

Hours, rates, assumptions, and tool spend in one ledger - weak savings become visible.

Governance-lite

Approval gates, data rules, and incident notes without enterprise GRC weight.

Client report

A white-label monthly report that gives the client a reason to renew the retainer.