Implementation Workflows
Dotnitron builds governed workflows around documents, ERP/source-system data, evidence, compliance, diligence, and reporting operations.
Workflow catalog
Choose the bottleneck with the clearest cost of delay and prove it with real artifacts, real users, and validation evidence.
Design governed AI agents around one recurring workflow, with approved tool access, source retrieval, human review, and validation evidence.
Extract control statements from client policies and map them to SOC 2, ISO 27001, HIPAA, or your firm control library.
Produce Covered, Partially Covered, and Missing verdicts with source-backed rationale your reviewers can inspect.
Review client evidence against control requirements and flag weak, missing, stale, or inconsistent support.
Draft ToD and ToE assessment notes from control descriptions, procedures, and client evidence for human approval.
Review data rooms, contracts, reports, and management files against your diligence playbook.
Export reviewer-approved findings into your Excel, Word, PowerPoint, or internal workpaper formats.
Let approved teams ask recurring operational questions over ERP and source-system data without waiting on analyst queues.
Turn candidate, vendor, and company verification documents into repeatable review workflows with evidence-linked outputs.
Automate recurring company law, filings, registers, board records, and compliance document checks for diligence teams.
Forward-deployed implementation
We start with the operating path: who asks, which data is approved, what sources must be visible, who reviews, and what output creates value. Then we build the AI system around that reality.
Governed by design
Outputs connect back to source documents, visible SQL, approved scopes, and reviewer decisions.
Capability Layers
InsightGale supports document-heavy workflows. SemeLabs supports governed ERP and source-system answers. Pelestra supports data readiness and sensitive repository review when private deployment or client data boundaries matter.
Turns policies, controls, evidence, contracts, reports, and data rooms into structured, source-visible review outputs for human approval.
A governed answer layer for complex ERP and source-system data where the hard problem is selecting the right tables, joins, definitions, and business context before SQL is written.
Discovers sensitive data, maps access risk, and prepares private repositories before AI is connected to regulated enterprise systems.
Evidence scattered across email, client portals, Slack, SharePoint, ticketing systems, and local folders.
A client-approved intake, AI-assisted review layer, human approval loop, and export into the workpaper format your team already uses.
InsightGale handles document-heavy workflows. SemeLabs handles governed ERP and source-system answers. Pelestra handles data readiness and sensitive repository review before AI enters the workflow.
Bring one painful process. We will map the operating path, data scope, controls, and proof needed for a practical pilot.