Compliance and evidence workflows
SOC 2, ISO 27001, control mapping, gap analysis, evidence review, ToD, and ToE support where outputs need reviewer approval.
Applied AI Consulting
Applied AI consulting that ends in production systems.
AI strategy is not enough. We help document-heavy, decision-heavy teams identify bottlenecks, evaluate models, and design secure workflows that go to production.
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.
01
AI strategy is not enough
Many enterprises are stuck in 'pilot purgatory'. They have slide decks and strategy documents, but no production systems. We bridge the gap between AI hype and enterprise reality by evaluating actual data readiness, security boundaries, and API integration paths before writing a line of code.
02
How Dotnitron identifies workflows worth automating
We don't automate everything. We map your operations to identify 'decision-heavy' and 'document-heavy' bottlenecks. If a workflow involves unstructured data ingestion, deterministic business rules, and a human review step, it is a prime candidate for an applied AI pipeline.
03
How Dotnitron evaluates models and services
We are model-agnostic. We evaluate the client's approved frontier models, private model endpoints, specialized OCR engines, table extraction tools, and embedding models to design a pipeline tailored to latency, cost, accuracy, and security requirements.
04
How Dotnitron designs secure workflows
Security is the architecture. We design systems that deploy into your existing AWS/Azure VPC. We diagram the data flow to ensure PII masking, enforce Row-Level Security (RLS) via injected user context, and ensure all AI inference happens within a private network boundary.
05
How Dotnitron moves from pilot to production
A prototype is easy; production is hard. We build scalable data ingestion pipelines (using tools like Airflow or Temporal), robust error handling, structured output validation (using Instructor/Pydantic), and React-based human-in-the-loop review interfaces to ensure the system is actually adopted by users.
Where This Applies
Start where repeated interpretation work is already hurting margin.
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.
Diligence and verification workflows
Data-room review, background verification, secretarial due diligence, and other document-heavy processes that need source-backed findings.
ERP and operational answer workflows
SQL-backed operational intelligence for teams that need recurring answers from ERP and source-system data without analyst queues.
FAQ
Frequently asked questions
What is applied AI consulting?
Applied AI consulting focuses on implementing AI technologies to solve specific business problems. Unlike general strategy consulting, it results in working software, integrated systems, and measurable operational improvements.
How do you choose which workflows to automate?
We look for 'decision-heavy' and 'document-heavy' processes. If highly-paid professionals are spending hours manually extracting data from PDFs or cross-referencing policies, that is a prime candidate for applied AI.
Ready to move beyond AI pilots?
Bring us one workflow where an AI agent could remove repeated analyst work without losing source visibility, controls, or human review.