Summary: “About 60 days to production” is a claim that invites a fair question: what happens during them? Here is the honest week-by-week of a MightyBot deployment for a regulated document workflow: what the platform does, what your team provides, and the evidence gates that decide when autonomy expands. No phase is filler, and the two weeks that most often stretch the calendar belong to access, not technology.
Weeks 1-2: Scope and policy encoding
The deployment starts with the work, not the software. One workflow is scoped precisely: which case types, which decisions, which exceptions. Then the governing rules come out of wherever they live today: credit policy PDFs, procedure manuals, the heads of senior reviewers.
Those rules become plain-English policies in the Policy Authoring Studio, drawing on a growing policy library as starting points rather than blank pages. Your compliance and operations leads read every policy, because they can: the policies are the artifact, not a translation of it. Where rules vary by jurisdiction or counterparty, profiles capture the variations without duplicating anything.
Your side: the documents that define the rules, and the people who know the unwritten ones. Two workshops, typically.
Weeks 3-5: Document calibration and integration
The document pipeline meets your real paper: the 200-page packages, the 150-DPI scans, the spreadsheets with merged cells. Classification and extraction calibrate against a representative sample of actual historical cases, with every extracted value carrying evidence pointers back to page and character.
In parallel, integrations connect the systems of record: the LOS or claims platform, document repositories, and the warehouse where compliance exports will land. Native connectors and standard APIs cover the typical stack; the workflow compiles against live data by the end of week 5.
Your side: the document sample and integration credentials. This is where calendars slip, and almost never for technical reasons: security review queues and access approvals are the long pole. Book them in week 1.
Weeks 6-7: Audit mode
The agent goes live in the least dramatic way possible: it processes real cases end to end, and nobody acts on its output. Humans keep deciding everything. Every agent decision is compared against the human decision it shadowed.
This is where the accuracy claim stops being a vendor number and becomes your number, on your cases, with a why-trail under each decision your team can inspect. Disagreements are the valuable part: each one is either an agent error (the policy gets refined and backtested) or, regularly, a human inconsistency the agent surfaced.
Your side: reviewer time to adjudicate disagreements. Hours per week, not headcount.
Weeks 8-9: Gated go-live
With audit evidence in hand, the workflow moves to assist mode: the agent prepares decisions and evidence, reviewers approve or override at review gates placed where your risk demands. Clean-case categories graduate to automation as the evidence supports it, and the platform keeps measuring how often reviewers change agent output, so autonomy expands on data, not on optimism.
Production, in other words, is not a switch. It is a gradient your compliance team controls, with the evidence to defend every step of it.
Why 60 days is possible, and when it is not
The timeline holds because the platform layers already exist: document intelligence, policy execution, audit infrastructure, integrations. The deployment is configuration and calibration, not construction. The same workflow built internally runs 12 to 18 months, because the layers have to be built before the workflow can exist.
And the honest caveat: 60 days assumes the three inputs show up (policies, documents, access). Deployments miss the window for calendar reasons, not capability ones. The ROI calculator prices what each month of delay costs; the short answer is that the queue you are automating keeps charging you rent until go-live.
