Two weeks. Workflow triage, hours-saved estimates, build-vs-buy decisions, six-month roadmap, kill list. Fifteen pages, not a hundred.
/ AI Automation Services /
AI automation that replaces the work, not the tools.
Most AI automation moves your manual process from one SaaS tool to a different one and calls that automation. Ours replace the work - vendor reconciliation, invoice routing, weekly reporting, CRM hygiene - with autonomous agents and hand the operator ten to thirty hours a week back.
Most AI automation tools move work between tools. Ours eliminate the work entirely.
Most automation agencies
Install a workflow tool and point it at the spreadsheet your operator was filling by hand
The spreadsheet is gone; the work isn't. Your operator is now copy-pasting from a new tool
A hundred-page vendor comparison that recommends nothing and ships nothing - RPA (keystroke-recording automation) versus middleware tools (iPaaS) versus everything else
A pilot that runs inconclusively for six months because nobody wrote down which hours were supposed to come back
Keystrokes-and-replay RPA that fails quietly next Tuesday when the SaaS tool updates its interface
JAAX Labs
One autonomous workflow live in your stack inside fourteen days, with hours-saved telemetry
An exception queue (a list of cases the agent flags for human review) your team owns, with role-based routing and audit logs for compliance
A prioritized list of which three workflows to automate and which six to leave manual
Hours-net dashboard measured before and after - the operator can read the savings on Monday
The same two engineers on your kickoff call are the ones writing the agent and on your Saturday-night triage
Four steps. Same every time.
Workflow Triage
Which workflows pay off
We kill the ones that don't before you spend on them. A written assessment per workflow against a fixed rubric - hours-per-week consumed, decision repeatability, data availability, exception rate, outcome ownership.
Eval Before Prompt
Ship the smallest useful thing
The eval (automated test suite that scores model output) is the spec. We write a hand-rated golden set of 20–40 examples per critical decision before we write a single prompt or wire a single integration. When we get this order right, we ship in days.
Production Hardening
Hours-saved dashboard ships first
Exception queues with role-based routing, idempotent handlers, cost caps per workflow, audit logs, feature flags on every new path. Hours-saved telemetry - net of exception-review time - shipped before the agent is interesting.
Team Enablement
Leave you self-sufficient
Runbooks for incident response and rollback, exception-policy documentation your team owns, training, and the README every junior operator should read on a Monday.
/ What you actually get /
One workflow live in 14 days. Hours tracked from day one.
One autonomous workflow in your stack by day fourteen. Hours-saved dashboard. Exception queue. Runbook. Team trained. No sandbox demos, no proof of concept (PoC) that never ships.
Book a fit call →AI Automation Engagement · Deliverable · JAAX Labs
AI Automation Sprint - Deliverable
01
Workflow Triage & Prioritization
Every candidate workflow with hours-per-week, ROI estimate, and red/yellow/green rating with written rationale.
02
Build vs. Buy Decisions
Specific vendors, models, integration costs, and exception-handling requirements per workflow.
03
Six-Month Rollout Plan
Which three workflows to automate next quarter, named owners, cost per workflow, risk assessment.
04
Kill List & Exception Handling
Projects we recommend stopping, with one-paragraph justification. Exception policies for the top priority.
05
Hours-Saved Dashboard & Runbook
Baseline measurement, target hours returned, telemetry spec, incident response procedures, rollback plan.
/ Engagements & pricing /
Four shapes. Ranges from $25k to $150k+.
Workflow count, integration surface, and exception complexity determine your shape. We publish ranges because the call where you ask the price and three weeks of email-tag begin - we hated being on that side of the table.
Fourteen days to one workflow live and saving measurable hours. Exception queue, eval harness, hours-net dashboard, runbook included. Refundable if it doesn't ship.
Six to twelve weeks. Multi-workflow portfolio, exception routing, audit logs, drift detection, cost controls, team handoff.
Senior engineers embedded with your ops or platform team. Architecture review, exception-policy design, on-call escalation. Quoted by scope.
/ How we know this works - Sentinel /
We eat our own cooking - Sentinel, our live analytics product, runs on agents.
Sentinel is JAAX's live Shopify analytics product. Every weekly report, anomaly alert, and operator question is handled by an agent because we are too small to do it ourselves. The engineering muscle that runs Sentinel is the same muscle that runs your engagement.
See Sentinel
12
automations in production
92%
renewal rate
14d
typical sprint
2
founders, no juniors
/ Who this is for /
Heads of operations, finance, RevOps, and support at mid-market companies.
The buyers we do our best work for are heads of operations, finance, RevOps, or customer support at mid-market and enterprise companies - roughly $50M to $500M in revenue, sometimes a single division inside a larger one.
Their teams spend 10–30 hours a week on manual work that an agent can replace. They have measured - or can within a week - that the work consumes those hours. And they have stopped tolerating the gap between vendor automation pitches and calendars that never clear.
If you need a hundred-page automation maturity assessment, a multi-quarter platform-evaluation phase, or a center of excellence with a charter - call a Big Four firm. We are not better at that than they are.
"The deliverable is hours. Not a system. Not a workflow. Hours back on the operator's calendar, measured against a baseline we wrote down before kickoff."
From the JAAX methodology
Questions we get on every fit call.
AI automation is the work of replacing a manual back-office workflow - vendor reconciliation, invoice routing, weekly reporting, CRM hygiene, support deflection, Slack-driven approvals - with an autonomous agent that does the work end-to-end and hands the operator hours back. RPA records keystrokes and replays them; iPaaS moves data on a schedule; AI integration wires a model into one surface. AI automation is the workflow itself, executed by an agent that reads the inputs, makes the call, writes the outputs, and routes the exceptions.
The workflows we most often automate:
- Vendor reconciliation against the general ledger (GL)
- Invoice triage and approval routing
- Weekly KPI report generation
- CRM hygiene jobs (deduplication, lifecycle-stage correction, ownership reassignment)
- Customer-support deflection at L1
- Slack-driven approvals
- Salesforce or HubSpot data-quality cleanup
The pattern is the same across all of them: a recurring decision a human is making by reading the same five fields and applying the same rule, where the rule is fuzzy enough that a deterministic script broke last time.
An automation strategy sprint is two weeks, no extensions. A production proof-of-concept is fourteen days from kickoff to one workflow live and saving measurable hours. A full implementation across multiple workflows is six to twelve weeks depending on how many surfaces touch the agent and how clean the existing data is. We refuse engagements that don't fit a two-week window at the unit level. If the work cannot be sliced into 14-day deliverables, we have not finished scoping it.
Strategy sprints run $25–45k. Production proofs-of-concept run $50–150k. Full implementations start at $150k and scale with the number of workflows and the integration surface. Embedded team augmentation is a monthly retainer. Pricing is uniform across our practice - we charge by engagement shape, not by domain. We also ask buyers to put a number on the hours-per-week the workflow currently consumes; if the math doesn't work against the hours saved, we say so before the contract.
Every automation we ship has an exception queue before it has a happy path. The agent's first job is to know which cases it should not handle and route them to the human who should, with enough context that the operator can decide in seconds. We tune the confidence threshold against a hand-rated golden set of 20–40 examples written before the prompt - refusal rate, false-positive rate, and false-negative rate are dashboard metrics from day one. The success metric is hours returned net of exception-review time, not percentage automated.
Hours-saved telemetry is a first-class metric. Before kickoff we measure baseline - operator self-report plus a one-week instrumented sample. After launch, the dashboard shows runs completed, exceptions routed, time-per-run versus baseline, and net hours returned per week. If the agent saves four hours but the exception queue takes six, the dashboard tells the truth and we redesign. We have killed two automations in week six this way.
Yes, mutual NDA before any technical conversation. We do not work for clients with conflicting active engagements in the same competitive set during a quarter - a rule we enforce on ourselves more strictly than most clients ask us to.
If you need a hundred-page automation maturity assessment delivered by analysts you'll never meet again, hire one of the four firms that sells that. If you need a workflow autonomously running by the end of the month and hours showing up on the operator's calendar the week after, hire us. The two-person constraint is the feature. The engineers writing the agent are the engineers on your kickoff call, your production cutover, and your Saturday-night exception triage.
Send a paragraph. We'll come back the same day.
Tell us which workflow is eating your operators' weeks and how many hours it costs. We'll come back with a yes, a no, or a sharper question. No discovery deck, no pitch meeting marathon.
Book a 30-min fit call