Custom AI products and systems
Turn a valuable business problem into AI your team can use.
Whether you need an internal agent, a customer-facing AI product, or a better way to use business data, we design and build the complete system and help your team put it to work.
Where we can help
Move from an AI idea to something people use every day.
You bring the business problem. We bring the product, AI, software, data, and deployment experience needed to solve it as one connected build.Give your team back time from repetitive work
Turn document review, research, reporting, and other recurring work into a reliable system that fits the tools and approvals your team already uses.
Explore this service ↗Launch an AI product people will actually use
Take a customer or employee need from idea to a complete product, including the experience, software, data, AI behavior, and launch support.
Explore this service ↗Add experienced AI builders to your team
Work alongside senior product and engineering specialists who can help you ship now and leave your team stronger after launch.
Explore this service ↗How we work with you
See progress in working software, not slide decks.
We start with the problem, build in short cycles, test with real users and data, and stay involved until your team is ready to run the system.Build
Put working software in your hands early.
We connect the models, data, business rules, interfaces, integrations, and safeguards, then show you real progress in short cycles.Built for complex, high-stakes work
When every answer has to stand up to scrutiny.
We help teams use AI where information is fragmented, expert time is limited, and people still need to understand and approve the result.Private equity
Diligence, portfolio intelligence, and value-creation decisions constrained by fragmented documents and operating data.
Advisory and consulting
Delivery margin lost to evidence intake, analysis, reporting, and repeated reviewer reconstruction.
BFSI, risk, and compliance
Customer and operating experiences that must respect access, residency, auditability, and regulatory boundaries.
Legal and compliance
Contract, policy, obligation, and case work where every conclusion needs defensible support.
Selected client work
See the systems we have helped put into use.
Explore enterprise AI, private-markets, and compliance projects, including what we built and where each system reached in its journey.
Production Enterprise AI
Enterprise generative AI platform across seven regional environments
Contributed retrieval, document processing, model integration, product engineering, testing, and production support across seven separately maintained regional environments.- 7 Regional Environments
- ~3,500 Registered Users
- OpenAI + Azure OpenAI
Production Private Markets AI
Private-markets intelligence platform deployed to five enterprise clients
Built frontend, backend, document retrieval, and multi-model capabilities for a private-markets platform deployed in five customer-controlled environments.- 5 Enterprise Deployments
- Customer-Controlled Infrastructure
- Multi-Provider AI
Validated Enterprise AI
Compliance and risk platform validated before deployment
Delivered an AI-enabled compliance and risk-management platform end to end. The customer has validated the build and uses it in prospect demonstrations while the first end-client deployment remains pending.- Validated Pre-Deployment
- End-to-End Delivery
- OpenAI + Azure OpenAI
- Source visibility or inspectable SQL
- Human approval before consequential action
- Role-based access and scoped tools
- Evaluation evidence before expansion
Reusable technology, tailored to your business
Start further ahead without being forced into a platform.
Our document, data, and AI building blocks help us move faster. We adapt them to your users, systems, security needs, and the advantage you want to create.Underlying
A reusable Dotnitron capability for agentic analysis of diligence files, policies, contracts, evidence, reports, and data rooms where outputs need source visibility and human approval.
See how it works ↗ERP and Operating Data Answer LayerSemeLabs
A reusable Dotnitron capability for SQL-backed answers from approved ERP, finance, and operating data when teams need visible logic and validation.
See how it works ↗Data Readiness LayerPelestra
A reusable Dotnitron capability for preparing messy, sensitive repositories before AI touches regulated enterprise data.
See how it works ↗A practical place to start
Choose one problem that matters.
Start with work that is painful enough to change, focused enough to build well, and important enough for someone in your organization to own.
- 01
Show us what is getting in the way
Tell us who is affected, how the work happens today, and what a better outcome would mean for the business. You do not need to share confidential material in the first conversation.
- 02
Agree on a useful first release
Together, we choose a focused starting point, decide how it should work, and make the scope, responsibilities, timing, and cost clear before development begins.
- 03
Build, test, and launch with your team
Your users see working software early. We test it against real situations, improve what falls short, support the launch, and measure how it performs.
Recognized by OpenAI for helping organizations build, deploy, and scale AI solutions.
Designed for responsible use
Your data follows agreed boundaries.Your people stay in control.Performance stays visible.
Review our security approach ↗Before we work together
What you may want to know.
What does Dotnitron do?
We design and build custom AI agents, products, and business systems. Our team can take a project from the first product decisions through software development, data integration, testing, launch, and support.
What can you build?
We build internal agents, customer-facing AI products, document and knowledge systems, data and decision tools, and the software that connects them to your business. The right solution depends on what your users need, the information involved, and where the system will run.
Is Dotnitron an AI agency or a software product?
Dotnitron is a product and engineering partner. We use our own reusable technology to move faster, but we work with you to build a custom result rather than forcing your problem into a generic platform.
Do you only build AI agents?
No. An agent may be part of the answer, but useful AI also needs a good experience, dependable software, the right data, integrations, permissions, testing, and a clear role for people. We build the complete system your users need.
Which organizations are the best fit?
We work best with organizations that have an important problem, someone ready to lead the change, and access to the people and information needed to build well. The project should matter enough that your team will use and measure the result.
How do you reduce delivery risk?
We keep the first release focused, agree on expected results, and test with realistic inputs and users. When mistakes carry real consequences, we make sources visible, limit what the AI can do, add reliable rule-based checks, and keep people in control.
How do engagements start?
In the first conversation, we learn who needs help, what happens today, what you want to improve, which systems are involved, and when you want to move. We then recommend discovery, a focused build, support for your existing team, or more preparation before you invest.
Can this run in a private environment?
Yes. Depending on the requirements, we can design for private cloud, tenant-isolated, client-controlled, or other approved environments with scoped access and data boundaries. The exact provider, retention, network, and model path is confirmed during architecture and security review.
How long does a project take?
A narrowly scoped production sprint can take several weeks. Larger products, complex integrations, regulated deployments, and multi-team programs take longer. We provide a clear plan, target dates, responsibilities, and commercial scope after we understand the result and constraints.
What should we bring to the first call?
Bring one meaningful problem or product opportunity, who experiences it, what happens today, why it matters now, the systems or data involved, and what a valuable result would change. You do not need to share confidential files during the first conversation.
Have a problem AI should be solving?