Document and statement intake
Extract fields from statements, invoices and onboarding documents, validate them against rules and route unclear cases to an analyst.
Industry
Technology that earns trust in finance.
Financial teams need software that is accurate, auditable and clear about what it did. We build systems and AI tools inside the controls your risk, security and compliance teams already require.
Overview
Controls and delivery, designed together.
Money moves through software that cannot afford quiet mistakes. A misread statement, a duplicate payment or an unexplained model output becomes a reconciliation problem, a customer complaint and an audit finding. Projects in this sector succeed when engineering and controls are designed together, from the first data model to the final audit log, rather than bolted on at the end. We treat the audit trail as a feature, not a report produced after the fact.
Our role is to build the software and AI features, not to replace your risk function. We work with your compliance and security teams to understand the rules that apply, design within them and produce the evidence they need to review a release. AI features stay narrow, explainable and supervised until the evidence supports anything broader. That keeps the boundary clear and the evidence honest. We would rather ship a smaller feature that passes review than a broad one that cannot.
Audit-ready by design
Every sensitive action is logged with actor, input and outcome, so reviews do not depend on reconstructing history later.
Data lineage you can follow
Pipelines that trace where each figure came from, how it was transformed and which system currently owns it.
Rules before models
Deterministic checks and clear policy stay in control, with models used only where they add measurable value.
Human approval where it counts
Payments, account changes and exceptions require a named reviewer, with the reasoning and supporting evidence attached.
Security as a requirement
Least-privilege access, encryption, secret handling and environment separation treated as core requirements, not optional refinements.
Documented for review
Architecture notes, model cards and test evidence written for the people who will audit the system, not just the people who built it.
Use cases
Work that fits the regulated path
Good first projects are narrow, measurable and easy to review.
Reconciliation support
Match transactions across systems, surface breaks with context and let staff resolve or escalate each case from one screen.
Servicing and support assist
Draft responses to routine account and product questions from approved content, leaving decisions about money and eligibility to staff.
Reporting and controls testing
Assemble recurring reports and control evidence automatically, with a clear record of the query, source and reviewer for each run.
How we work
How we deliver in a regulated setting.
Discover
We start with the control requirements, not the code: which rules apply, who reviews releases and what evidence must exist.
Design
We design the data flow, permissions and review points with your security and compliance teams, and write the decisions down.
Build
We build in small, reviewable increments, with tests, logs and documentation produced alongside the feature rather than afterward.
Support
We hand over with runbooks, monitoring and a clear change process, and stay available for audits and production questions.
FAQ
Common questions.
Can you work with our compliance and security teams?
Yes. That is the normal way we start. We join their reviews, document the design decisions and adjust the scope so it fits the controls you must meet.
Do you build the compliance program for us?
No. We build software that works within your program and help produce the technical evidence your team needs. Certification and regulatory decisions stay with your organization.
How do you decide whether an AI feature is safe to use?
We define the decisions the feature does not make, test it on representative cases and keep a person in the loop until the results justify more autonomy.
Can the system run inside our own environment?
Yes. We can deploy to your cloud account or data center, and we can use model providers that meet your data handling requirements. Your security team keeps the final say on where data lives.
Next step
Start the conversation
Planning change under tight controls?
Share the constraints you work within and the outcome you need. We will suggest a first step that your reviewers can support.