About

We build production AI systems for high-stakes expert work.

Our market wedge is PE and M&A transaction advisory. Our durable capability is turning ambiguous, document-heavy business processes into reliable multi-agent systems without removing the experts, evidence, and controls that make the work trustworthy.

Why founder-led matters

The people mapping the process are the people building the system.

For confidential PE and advisory work, context gets lost when discovery, engineering, and delivery are separated. Dotnitron stays close to the actual work: source material, reviewer judgment, security boundaries, and the output your team needs to approve.

Founder-led delivery

You work directly with the senior builders who map the process, establish the baseline, design the system boundary, build the product, and stay close to reviewer feedback through go-live.

Transaction and advisory context

Our approach is shaped by private equity and large advisory environments where diligence files, spreadsheets, workpapers, client evidence, and review standards must be handled carefully.

Real engineering ownership

We own the software, multi-agent architecture, deterministic checks, integrations, evaluation, deployment path, review layer, documentation, and handover.

Our DNA

We are builders first.

We write the actual code and configure the actual security infrastructure. No outsourcing.

Grounded in operational reality.

Our standards are shaped by what it takes to keep a system running in production, not what looks good in a pitch.

Our Conviction

Weturnanalyst-heavy,high-stakesexpertworkintoreliablemulti-agentsystems,startingwiththedeal-deliveryprocessesthatconstraintransactionadvisorycapacity.

The goal is dependable capacity: work your team can inspect, edit, approve, and deliver through the firm's existing operating model.

What is Dotnitron

A specialist implementation partner for firm-specific agentic AI.

Dotnitron helps advisory teams turn diligence files, spreadsheets, firm knowledge, evidence, and approved tools into coordinated multi-agent systems with traceable outputs, human review, and measurable operating evidence.

What Dotnitron is

A specialist build partner for teams with recurring review work, proprietary templates, client delivery standards, private data, and approval processes.

  • Reusable capability layers where they accelerate delivery
  • Reviewer-ready outputs with sources
  • Private deployment and approved tool connection options

What Dotnitron is not

We are not a generic AI agency, a model provider, or a tool that leaves your team to solve workflow adoption alone.

  • Not a replacement for your business judgment
  • Not a chatbot project
  • Not a public-model data shortcut

Our Operating Principles

Clarity on what Dotnitron is and what it is not.

No

What we don't do

  • Force your team into a generic finance or AI platform
  • Replace senior reviewer judgment
  • Send unsupported AI conclusions to clients
  • Build broad demos disconnected from deal delivery
  • Ignore your templates, review notes, or methodology
Yes

What we deliver

  • Agentic systems around your deal-delivery process
  • Reviewer-ready outputs with traceable sources
  • VDR review, diligence, workpaper, and data-extraction automation
  • Human approval flows before client delivery
  • Private, client-approved deployment options
  • A shadow run, clear handover, and measurable operating evidence

What defines us

Principles we build reliable agentic systems by.

01

We build around the operating reality of the client: people, tools, data boundaries, review loops, controls, and decision owners.

02

We do forward-deployed applied AI work, not demo chatbots disconnected from delivery.

03

We design for source-visible outputs, visible SQL where relevant, audit trails, client confidentiality, tool connections, and private deployment options.

04

We start with one painful workflow, prove measurable value, and expand only when the team trusts the output.

OpenAI Select Partner

OpenAI partner network

Build with an OpenAI Select Partner.

Recognition supporting our work helping organizations build, deploy, and scale production AI systems with OpenAI.
Review deployment controls

Ready for a production decision

Ready to increase capacity in one deal process?

Start with one repeated, analyst-heavy process and prove the operational value in a focused 6–8 week Agentic AI Production Sprint.