Compliance and evidence workflows
SOC 2, ISO 27001, control mapping, gap analysis, evidence review, ToD, and ToE support where outputs need reviewer approval.
Workflow Automation
We remove manual extraction, routing, reconciliation, and first-pass analysis from workflows that still need source visibility, access control, and human review.
What is Dotnitron? Dotnitron is a forward-deployed AI workflow implementation company. We help teams turn AI models, agents, internal data, documents, ERP systems, and human review processes into secure production workflows with measurable operating value.
We target workflows where humans act as routers or data extractors: reading complex emails to update Salesforce, pulling tables from PDFs into Excel models, or cross-referencing vendor contracts against procurement playbooks.
Traditional RPA breaks when a document format changes or an email is phrased differently. AI-assisted workflows can extract structured data from unstructured text, apply deterministic business logic, and route approved actions through existing APIs.
We do not design unsupervised agents for sensitive operations. We build review screens that show confidence signals, anomalies, source citations, and proposed actions so human experts can validate before records are updated.
Every automated workflow is state-managed. We capture inputs, prompts, model responses, structured outputs, reviewer actions, and approval decisions so teams can inspect how important outputs were produced.
Where This Applies
The best AI agent implementation projects do not begin with a blank transformation program. They begin with a workflow that already has volume, rules, exceptions, reviewer judgment, and measurable delay.
SOC 2, ISO 27001, control mapping, gap analysis, evidence review, ToD, and ToE support where outputs need reviewer approval.
Data-room review, background verification, secretarial due diligence, and other document-heavy processes that need source-backed findings.
SQL-backed operational intelligence for teams that need recurring answers from ERP and source-system data without analyst queues.
FAQ
AI workflow automation uses models, retrieval, business rules, integrations, and human review to prepare or execute repeatable work involving unstructured inputs, decisions, and source checks.
We use human-in-the-loop design. The system prepares extraction, comparison, and draft outputs with citations, then routes them to the right reviewer before they become final.
Bring us one workflow where an AI agent could remove repeated analyst work without losing source visibility, controls, or human review.