Data access requirements
Define who can access which information and how it may be handled before implementation.
Software for financial and advisory firms
Kairon Insights develops and supports software for document-intensive financial and advisory work. Models, document processing, and data storage run within your enterprise environment, keeping confidential client information and material nonpublic information (MNPI) under your control.
Designed for local deployment under your security policies.
One discrepancy held for reviewAdjusted earnings need the team’s judgment.
Financial &
professional services
For fully local client deployments
Local processing and storage, without cloud AI services.
Core processing operates without an internet connection.
External services introduce additional data-handling and vendor-review requirements. In a fully local deployment, documents, model inference, and outputs remain within your organization’s infrastructure.
These workflows do not require public-facing application endpoints or external AI APIs. They can operate in isolated environments configured for that purpose, reducing exposure associated with third-party processing and storage.
Workflow examples
Financial document processing requires accurate entity, period, and version identification. We build those checks into software that follows your reporting templates and review requirements.
Search engagement folders by document type, entity, and period, with links to original files and version exceptions.
Explore this workflowCIM_v2 identifies the same year. Its name alone does not establish which version to use.
Illustrative paths. Authoritative files stay in place.
/Engagements/Company_A/02_Financials/Company_A_CIM.pdf
/Engagements/Company_A/Received/Sept/Company_A_CIM_v2.pdf
/Engagements/Company_A/02_Financials/FY2025_statements.pdf
Populate deal templates with extracted figures, source locations, and exceptions for review.
Explore this workflow| Requested field | FY2025 | Source |
|---|---|---|
| Revenue | 84.2 | CIM · p. 24 |
| Reported EBITDA | 12.6 | CIM · p. 25 |
| Adjusted EBITDA | Review | QoE · p. 18 |
Adjusted EBITDA is held for reviewConflicting adjustment totals. No value accepted.
Each mapped field keeps its reporting period, units, and source reference in the workbook.
CIM_v2 remains unconfirmed in the document register. It does not silently replace the selected source.
12.6 reported + 1.5 / 1.2 in adjustments. The bridge needs confirmation.
QoE reports adjusted EBITDA of 14.1; the operating model shows 13.8. Confirm the adjustment bridge before using either figure.
Awaiting professional review. Neither figure is accepted into the workbook.
Compare company submissions in a consistent format while missing reports and unit differences stay visible.
Explore this workflowRevenue increased from 20.4 to 21.8 USD million. Both periods are attached for the reviewer to check.
Company_A_Q1_2026.pdf · p. 3 / Company_A_Q2_2026.pdf · p. 3Connect the request list to the files received, so the team can see what is still outstanding.
Explore this workflowThe file matches the requested year. A proposed “received” status records delivery; the team still reviews the substance.
Illustrative workflows using sample data. Implementation is scoped to each firm’s requirements.
Development and ongoing support
Kairon provides workflow design, integration, deployment, and ongoing support. Maintenance includes agreed changes to reporting templates, document formats, and business rules, with priorities and release requirements established with your team.
Files, review points, and the output your team needs.
Representative documents, unusual cases, and agreed criteria.
Integration, support, and improvements within the agreed scope.
The quarterly template is mapped to the company reports.
Review and accountability
We define access, data handling, and review requirements with your team before implementation.
The scope specifies permitted data sources, how results are delivered, and which decisions require professional approval.
Define who can access which information and how it may be handled before implementation.
Design outputs so reviewers can trace a figure to its file, period, and source location.
Make missing information and conflicting figures visible at the point of review.
Fit the output to the team’s templates and tools, with professional sign-off built into the process.
The economics of local AI
Local inference uses your compute capacity without cloud-model API token charges.
Compare deployment approachesCloud API-based workflows incur model-provider usage charges, alongside any product fees. Kairon’s fully local deployments run models on client infrastructure, eliminating external model API charges for that processing.
Once the infrastructure is installed, additional processing uses available local capacity. For recurring, document-heavy workflows, this can reduce the cost of processing additional work.
Total costs include hardware, electricity, maintenance, and support. Savings depend on workload, utilization, hardware, and model requirements. Model quality and speed are evaluated against the requirements of each workflow.
Project inquiries
Share an overview of your current process, data sources, and required outputs. We can assess the scope, integration requirements, and deployment options.