Put AI where yourbusiness gets stuck.
We build AI into the jobs that slow your team down and cost you money, then show you what it's worth in hours and dollars.We map the workflow, connect it to your systems (API where there is one, browser automation where there isn't), run the repeatable steps as agents that follow your approval rules, and log every run, model and dollar to an ROI dashboard your finance team can pull themselves.
The money leaks out while work waits.
Work sits in someone's inbox. Answers live with one person. Decisions go out unchecked. Pick one and see what it costs.
None of that is a model problem. It is a work-clarity problem.
We don't count agents deployed. We count which of these six numbers moved.
Every Xsparks workflow has to move at least one. Your finance team agrees on the definition before anything ships.
- 01↓
Cost down
Less time and money spent on repetitive operating work.
- 02↑
Revenue up
Fewer missed follow-ups, faster quotes, and better renewals.
- 03↑
Hours back
Routine work comes off your team's desk, permanently.
- 04↑
Capacity up
More output without automatically adding headcount.
- 05↑
Quality up
Fewer errors, less rework, fewer escalations landing on someone's desk.
- 06↓
Risk down
Every step gated, logged, and traceable so you're always in control.
Think. Build. Operate.
Three steps, and none of them are complicated. Click any step to see it.The same three steps, the way your systems person will ask about them.
- 01 · Think
We learn how your business actually runs.
Your customers, products, people and rules, taught to it in one place. Then the right AI for each job, on your own accounts, at cost. We never mark it up.
A governed context layer, and a model chosen per task.
Your documents and CRM/ERP records become a versioned context store in your own cloud account. Whole documents never reach a model. Each task routes to the model that passes its eval, on API keys you hold.
Live Xsparks platform · sample workspace data
- 02 · Build
We build it into the work.
Real jobs running across the systems you already use, even the fifteen-year-old one with no clean API.
Agents that act through APIs, and through the browser where there is no API.
Connectors for common ERP, CRM and email, plus a browser worker for legacy systems. Every run is traced end to end, and one kill switch stops any workflow mid-run.
Live Xsparks platform · sample workspace data
- 03 · Operate
We run it, and you stay in charge.
You set the dollar limit. Above it, nothing moves until a person says yes. Every run is on the record, and anything stops the second you want it to.
Spend limits, a review queue, and an audit trail on every run.
Dollar limits by company, team and provider, enforced at the router. Work that needs a person lands in a review queue. SSO with role-based access, and every run logs who, which model, which inputs and outputs.
Live Xsparks platform · sample workspace data
+38 contexts · pricing rules v3 · versioned, roll back in one clickSales · run started · Quote build from spec sheet · 4 systems
INV-1048 approved by J. Morales · 14 pending → 13Every workflow.What it costs.What it returns.Where it stops.
One screen: what each piece of work costs down to the token, what it put back, who's using it, what's waiting on approval. If you can't state your AI return in dollars today, this is what's been missing.Per-run cost attributed to workflow, team and user automatically. Nobody tags anything. Read-only for finance. Exports to CSV. Your data, in your tenant.
The ROI Dashboard is the Xsparks screen that shows what every workflow costs, what it returns, and what still needs a human's approval.
Built for finance. Clear enough for the board. See the full ROI Dashboard →
| Workflow | Status | Runs / mo | Model cost | Hours off desk |
|---|---|---|---|---|
| Renewal desk, tier 2 accounts | Live | 1,284 | $412 | 96 |
| Quote build from spec sheet | Live | 640 | $1,109 | 143 |
| Field ticket to invoice | Live | 2,970 | $338 | 61 |
| Vendor onboarding pack | Awaiting approval | 0 | $0 | 0 |
- Agents built for your business. Sales follow-up, call handling, reporting, finance ops. Built, not bought off the shelf.Per-run cost accounting. Model, provider, task, workflow and user on every run, rolled up to team and company with nobody tagging anything.
- Cost and usage by team. See exactly who's using what and what it costs, down to the token.Return in your finance team's terms. Saved hours, captured dollars and avoided rework, computed from the method your finance team signed before the build.
- Return in dollars, not guesses. Every agent's output tied to a number your CFO will accept.Your own audit trail. Who triggered what, on which model, with which inputs and outputs, pulled whenever you want it.
- Humans on every decision that matters. Approval gates engineered in, not bolted on. AI never runs unsupervised where it counts.Export everything. Runs, costs and definitions to CSV. Any other connector we build if you need it.
Seen the ROI Dashboard. Now bring us the workflow that costs you the most.
Where the outcome can be measured, part of our fee sits on it.
Agreed up front, capped both ways, trued up every quarter. Ask any AI vendor what happens to their invoice when the outcome misses. Then ask us.The outcome share is defined in the SOW: the metric, the source tables, the exclusions and the cap, in both directions. If a baseline can't be measured from your systems, that workflow runs on a flat fee instead. No blended numbers.
- 1.1The baseline is yours, before we touch anything.
Trailing twelve months, agreed in writing in week one. A baseline set after we start means nothing.
Baseline extracted read-only from your ERP and CRM.Trailing twelve months, pulled by query with your finance team watching, signed as an appendix to the SOW.
- 1.2Your finance team owns the definitions.
They decide what counts as a saved hour or a captured dollar, and sign the method before anything ships.
The measurement method is a written spec.Source tables, definitions, exclusions and review cadence. Your finance team edits it before anything ships and can rerun it without us.
- 1.3The six numbers, every ninety days.
Not an activity report. The same review shown on the right, for every workflow, signed by your own finance team.
The quarterly true-up runs from the same spec.Same query, same definitions, ninety days later. The fee share is capped in both directions and stated in the SOW.
- 1.4One primary outcome per workflow. Nothing counted twice.
Hours back, cost down and capacity up can be the same benefit three times. Each workflow gets one finance-agreed primary outcome and at most two supporting indicators.
One primary metric, up to two supporting, no overlap.Finance signs the formula, source tables, exclusions and review cadence before the build. The same benefit is never counted under two labels.
- 1.5You own your data, your prompts and whatever you built.
Data, logs, and the agents and prompts your team configured leave with you in full. The platform is licensed, so our code and the workflows we ship on day one stay ours. Nothing of yours is locked to us.
| Number | Baseline · TTM | This quarter | Signed by |
|---|---|---|---|
| ↓Cost down | $48.2k / mo | $41.9k / mo | Client finance |
| ↑Revenue up | $1.20M pipeline | $1.34M | Client finance |
| ↑Hours back | not tracked | 300 hrs | Ops lead |
| ↑Capacity | 14 quotes / wk | 41 quotes / wk | Ops lead |
| ↑Quality up | 6.1% rework | 1.8% | Client finance |
| ↓Risk down | 0 gated | 14 gated · 147 auto | Owner |
We're not consultants.We ran the companies.
Ask any firm what they built. We were operators long before any of this was called AI, and we had this problem in our own businesses first.
What every published Xsparks result must include.
A number without these five things is marketing.
- 1Company, or approved contextNamed, or described in terms the client signed off.
- 2BaselineTrailing twelve months, agreed before we start.
- 3Date rangeWhen it was measured, start to end.
- 4Measurement methodHow the number was counted, in writing.
- 5Client finance sign-offTheir finance team's signature on the number.
33+ years in enterprise IT and AI transformation. Founder and CEO of Mindmatrix. Formerly EY and IBM.
AI researcher and founder of Nervesparks. Builds safety-first AI for defense, healthcare and energy.
30 years in enterprise software and partner ecosystems. Owns the quarterly review and the six numbers.
Founder who has built and run his own companies. Leads go-to-market and the live workshops where owners learn to put AI to work.
Find out where you actually stand.
12 questions. Under 3 minutes. Your score on screen, no sales call unless you ask. Your weakest area is your real level, and the readout tells you what to fix first.
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