Advisory workpaper preparation
Prepare source-linked drafts around a control library, evidence standard and reviewer template.
AI workflows and automation
Turn recurring requests, documents and reporting into a connected process. Dotnitron assesses the work, builds the integrations and adds AI where varied inputs need interpretation.
From workflow assessment to working software. Our workflow automation consulting service identifies where work waits, repeats or needs review. We then design and implement the agreed process across approved systems, with business rules, exception handling and human approval.
Map the current process with its owner. Record preparation effort, waiting time, missing inputs and reviewer corrections. Choose one valuable constraint that a working release can address.
AI can interpret documents, messages, and other inputs. Business rules, permissions, integrations, and workflow state define what may happen next. We test the complete process, including exceptions and human approvals.
We design review experiences that show sources, exceptions, confidence signals, and proposed actions. Your experts focus on decisions and edge cases instead of spending their time preparing every input by hand.
We define the baseline and track the measures that support an investment decision, such as cycle time, reviewer effort, exception rate, adoption, and output quality. Expansion follows evidence, not demo enthusiasm.
Where this can help
Prepare source-linked drafts around a control library, evidence standard and reviewer template.
Explore request intake, case preparation and reporting workflows with explicit review responsibilities. These are illustrative opportunities.
Explore how approved updates, gaps and report drafts can move through a consistent process. These are illustrative opportunities.
Your first release
Define the inputs, system connections, manual steps and approval points. Identify which steps need AI and which can use ordinary software rules.
Connect approved inputs to a usable work queue or output. Include missing-information checks, exception handling and the agreed review steps.
Your users try representative cases. Review the results, document how the workflow operates and agree who owns support after launch.
Compare preparation time, turnaround, reviewer edits and failure cases with the current process. Agree which measures matter to your team; savings depend on the workflow and are not guaranteed.
Choose the right approach
| Approach | Useful when | Check before choosing |
|---|---|---|
| Existing software | A product already covers the process and your team can adopt its workflow. | Data access, exports, approval steps, licensing and the effort needed to configure it. |
| Configured automation | The task follows stable rules and supported connections can move the data. | Connector limits, retries, exception handling and who maintains the automation. |
| Custom software with AI | Work involves varied documents, firm-specific logic or a review interface your team needs to control. | Representative test cases, approved model use, integration effort and ongoing ownership. |
Relevant delivery experience
Dotnitron delivered an AI-enabled compliance and risk platform end to end. The customer validated the build and uses it in prospect demonstrations; the first end-client deployment remains pending.
Read our role and delivery statusFAQ
It connects AI, business rules, approved data, software integrations, and human approvals to help complete a recurring process. We agree which steps can be automated and which need review.
We narrow the first release, establish a real baseline, test against representative examples, expose sources and exceptions, and place human approval at the points where errors have meaningful consequences.
Stable inputs and clear rules may be handled by conventional software or configured automation. AI can help interpret varied documents and messages. We assess the process first and choose the simplest approach that meets your requirements.
We assess approved APIs, data exports, permissions and supported integrations. Connector availability and the work required are confirmed during scoping; we do not assume every system can be connected.
The scope, number of integrations, data quality, review requirements and deployment environment determine effort. We agree on the first release, acceptance criteria, cost and timing before development. There is no standard savings or delivery guarantee across all projects.
Describe the recurring process, who owns it, where it gets stuck and the output you need. A non-confidential example or description is enough to begin. Approved sample data and access can be arranged after scoping.
Technology partnership
Have something in mind?