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Services

m00labs takes a concrete business problem and decides with you what it needs: a scoping conversation that ends in an honest verdict and a roadmap, or an automation, custom integration or full MVP that ends in working software. The work is organised into four practice areas, sold as five fixed-scope packages.

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System architecture

How the pieces of an m00labs build fit together

Illustrative concept
Inputs Email or inboxDocuments, requests,threads Webhook or APIAn event from a system yourun Scheduled jobA recurring batch or report Nothing connects until the scope says it does. Orchestration layer RouterDecides the path peritem ValidationShape and requiredfields Model callLanguage orjudgement step Retry queueBackoff, then aperson Write stepConfirmed results only Systems of record CRMWhere the customer recordlives Ticketing or inboxWhere the work is tracked Database or warehouseWhere the numbers live Observability LogsEvery run and every failure MetricsThroughput and error rate AlertsA break surfaces, not hides the build reports on itself
01InputsEmail or inbox, webhook orAPI event, and scheduledjobs — the three ways worknormally arrives.02Orchestration layerA router, a validation step,the model call, and a retryqueue that hands anythinguncertain to a person.03Write stepOnly confirmed results arewritten back, into thesystems of record youalready run.04Systems of recordCRM, ticketing, database orwarehouse — the record oftruth stays where your worklives.05ObservabilityLogs, metrics and alertsship with the build, so afailure surfaces instead ofdisappearing.
  1. InputsEmail or inbox, webhook or API event, and scheduled jobs — the three ways work normally arrives.
  2. Orchestration layerA router, a validation step, the model call, and a retry queue that hands anything uncertain to a person.
  3. Write stepOnly confirmed results are written back, into the systems of record you already run.
  4. Systems of recordCRM, ticketing, database or warehouse — the record of truth stays where your work lives.
  5. ObservabilityLogs, metrics and alerts ship with the build, so a failure surfaces instead of disappearing.
Illustrative concept — not a client system. The components shown are the ones a scoped build normally contains: where work arrives, the layer that decides and calls a model, the write back into your systems, and the monitoring that keeps it honest. Which systems sit on each side is decided with you in kickoff; nothing is connected until the scope says it is.
  • Data path
  • Reported by the build

AI strategy & roadmaps

Figure out honestly whether and where AI earns its keep in your operations — then get a build-ready roadmap. Two entry packages: the AI Clarity Session and the AI Opportunity Audit + roadmap.

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Automation & Integration Sprint

One production workflow or integration, engineered end to end inside the tools you already run — with error handling, logging, monitoring and handover documentation included.

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MVP Build

A working MVP with AI wired into your real data and systems — spec, architecture, build, tests, documentation and a production deployment your team can operate.

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ongoing AI Lab Partner

A standing engagement that keeps your automations, integrations and products running well and improving — regular strategy reviews plus a defined build allocation.

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Not sure which service fits?

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