Built for financial and professional services teams
AI-powered software, built around your business.
We design, build and integrate AI-powered tools, systems and products around your processes, data and existing systems—from understanding the problem to putting the software into use.
- Banking & insurance
- Private equity & investment
- Advisory & professional services
Where work limits growth
Growth should not depend on more manual effort.
Repeated preparation, disconnected systems and review bottlenecks keep delivery tied to people’s hours. We identify the constraint, then automate the right work or build the tools your team needs.AI workflows and automation
Connect your existing tools to reduce repeated preparation, data entry and handoffs, with exceptions and approvals routed to your team.
Explore this service ↗AI-powered tools and products
Build internal tools or customer-facing applications that combine AI with your business rules, data, and review requirements.
Explore this service ↗Software and AI engineering
Work with senior engineers to improve an existing product, connect AI services, or take a prototype through testing and launch.
Explore this service ↗How we work with you
Work directly with the team building your system.
Review working releases, test them with your users, and make product and technical decisions with us throughout the build.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.Teams we build software for
Built around the way your sector works.
Dotnitron designs and builds AI-powered tools, systems and products for banking, insurance, investment and advisory teams. We work around your processes, existing systems, data requirements and review responsibilities.Banking and financial institutions
Service requests, operational reporting, and connections between systems.
Insurance operations
Claims intake, case preparation, and policy-servicing workflows.
Private equity and investment
Deal research, investment analysis, and portfolio reporting.
Advisory and professional services
Engagement delivery, workpapers, and client reporting.
Banking and financial institutions
Customer and internal requests arrive through different channels. Teams re-enter details, search for context, and chase the next handoff.
Connect intake to your existing systems, identify missing information, and route the request with the context the next team needs.
Less repeated data entry. Clearer ownership of each request.Explore AI for banking and financial servicesExample workflow
- 01Receive the request
- 02Check approved system information
- 03Flag missing details
- 04Route the next task
Your team reviews the work and decides what to act on.
Insurance operations
Claims and servicing teams collect the same case details across emails, documents, and systems before they can act.
Organize incoming case material, track missing items, and prepare a summary for the person handling the claim or service request.
Better-organized case information. Fewer missing-item follow-ups.Explore AI for insurance operationsExample workflow
- 01Collect case material
- 02Organize the case details
- 03Track missing items
- 04Prepare a case summary
Your team reviews the work and decides what to act on.
Private equity and investment
Portfolio updates arrive in different formats. Analysts reconcile figures, chase gaps, and rebuild the same reports each cycle.
Bring approved updates into a consistent reporting workflow, flag gaps, and prepare a report with its supporting information.
Less reporting assembly. More time for analysis.Explore AI for private equityExample workflow
- 01Collect portfolio updates
- 02Align reporting fields
- 03Flag gaps and exceptions
- 04Review the report draft
Your team reviews the work and decides what to act on.
Advisory and professional services
Each engagement repeats the same preparation and follow-ups, while senior reviewers carry the sign-off load. More mandates put more pressure on the same team.
Build client intake, workpaper preparation, and review steps around your methodology, with open items tracked in one workflow.
More capacity for client delivery. Review stays with your team.Explore AI for advisory firmsExample workflow
- 01Organize engagement inputs
- 02Apply the firm's workflow
- 03Prepare work and follow-ups
- 04Route to the reviewer
Your team reviews the work and decides what to act on.
Illustrative workflows. Each project’s scope, safeguards, and expected results are agreed before we build.
Selected client work
Explore our client work.
Enterprise AI, private-markets intelligence, and compliance systems—with our contribution and the stage each project reached.
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 users recorded (Aug 2025)
- OpenAI + Azure OpenAI
Production Private Markets AI
Private-markets platform live in five client environments at engagement end
Contributed frontend, backend, document retrieval, and multi-model capabilities within a wider team. Five customer-controlled deployments were live when our engagement ended.- 5 deployments at engagement end
- 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
- Supporting information you can inspect
- Human approval before consequential action
- Access aligned with user roles
- Testing before wider rollout
Our products
Products built around real work.
Explore products for document workflows, business data, sensitive-data discovery, regulatory intelligence, and actuarial reporting. We help you assess whether a product or a custom build fits your requirements.Underlying
Analyze diligence files, policies, contracts, and workpapers with supporting sources and human review.
See how it works ↗Answers from business dataSemeLabs
Query approved ERP, finance, and operating data with visible SQL and checks on the results.
See how it works ↗Sensitive-data discovery and reviewPelestra
Discover sensitive data, inspect exposure and lineage, and record review decisions across connected sources.
See how it works ↗Regulatory intelligenceRegoscope
Follow regulatory publications, compare editions, inspect cited evidence, and prepare interpretations for review.
See how it works ↗Controlled actuarial reportingRepdate
Connect approved workbook figures to recurring Word reports, with source evidence, material changes, and independent checking in view.
See how it works ↗A practical place to start
Start with one problem worth solving.
Start with a constraint that affects capacity, turnaround or quality; a product opportunity with clear users; or an existing initiative that needs a path into use.
- 01
Show us what is getting in the way
Describe what is taking too much effort, where work gets stuck, or what you want to build. Bring the context and the outcome you want; confidential files can wait.
- 02
Agree on a useful first release
Together, we choose a focused first step and agree on the scope, responsibilities, timing, cost, and how to judge the result.
- 03
Build, test, and launch with your team
Your users try working releases early. We test realistic situations, address failures, and support rollout and handover.
We design and integrate OpenAI services within your approved architecture.
Designed for responsible use
Your data follows agreed boundaries.Your team controls key decisions.Tested against real work.
Review our security approach ↗Before we work together
What you may want to know.
What does Dotnitron do?
Dotnitron designs, builds and integrates AI-powered tools, systems and products for banking, insurance, investment and advisory teams. Projects include workflow automation, internal applications, customer-facing products and support for existing engineering teams.
Which businesses do you work with?
Our focus is banking, insurance, private equity and investment, and advisory and professional services, including related finance, risk, and compliance teams. Visit our client work for examples of our delivery experience.
What kinds of problems can you help solve?
Common goals include more delivery capacity, shorter turnaround, less rework and better access to information. We may automate a workflow, build a product or connect existing systems. The approach depends on the business problem and how your team will judge the result.
Do we need a defined AI project before speaking to you?
No. Bring the problem or product opportunity, who it affects, and what you want to improve. We will help you assess the options and choose a practical first step.
Can you work with our existing systems and engineering team?
Yes. We can integrate with approved tools, data sources, and APIs, and work alongside your engineers. We agree on access, ownership, and support responsibilities before development.
How do you handle sensitive data and deployment requirements?
We agree on data scope, permissions, application hosting, model-service processing, and retention for each engagement. Options can include private cloud, customer-controlled infrastructure, or approved hybrid arrangements. Application hosting and external model processing are reviewed separately.
How does a project start?
We first understand the problem, users, existing systems and current process. Together, we agree on scope, responsibilities, timing, cost and acceptance criteria. Some projects begin with discovery; workflow builds can include testing alongside the current process before rollout.