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Discover
Map the current process, owner, volume, friction, systems, data sensitivity, and baseline.
Forward-deployed methods, small-business scope
Dapols helps you find one valuable workflow, design the right model-agnostic stack, deploy it with human approval, and measure whether it increased revenue, reduced cost, or mitigated risk.
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Map the current process, owner, volume, friction, systems, data sensitivity, and baseline.
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Choose a model-agnostic stack, directional scope, exclusions, approvals, evaluation, and fallback.
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Implement one bounded workflow and compare it with the current process before go-live.
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Document ownership, monitor the target metric, handle edge cases, and hand over maintainable artifacts.
Boundaries build trust
Clear ways to start
$29 once
A self-service plan with workflow, stack, evidence, approvals, skills, and setup.
See details$199
A human reviews the workflow, assumptions, architecture, risks, metric, and directional scope.
See details$1,500 founding
Up to three standard SaaS integrations, approved handoff, and 14 days of stabilization.
See detailsIt is a hands-on delivery model in which technical people work closely with a customer to understand a real workflow, adapt technology to its constraints, deploy it, measure it, and leave maintainable artifacts behind.
No. Dapols productizes discovery, planning, evidence, workflow tracking, and monitoring for scoped small-business use cases. Complex enterprise systems, novel production code, regulated deployments, and high-risk decisions still need qualified people.
Depending on the offer, you receive a ranked workflow, model-agnostic stack, dated price evidence, assumptions, prompts, skills, connectors, approval points, evaluation checklist, deployment steps, and handoff guidance.
Do not use it as an autonomous operator for sensitive systems, a substitute for legal or compliance advice, or an open-ended engineering team. Start only when one workflow, owner, baseline, target, systems, and human approval path can be defined.
Further reading: OpenAI on enterprise AI deployment · AWS generative AI implementation guidance