Reconciliation and month-end close
Match transactions across ledgers, statements and source documents, then surface exceptions for a person to investigate.
AI for finance teams.
For finance teams, accounting and audit firms, and financial institutions. We build AI systems for document-heavy finance work that needs reliable results, clear evidence and human approval.
Book a 30-minute sessionWhere we start
Statement and invoice extraction
Extract information from statements and invoices, validate it against supporting documents and route uncertain cases for review.
Audit automation
For audit firms: prepare working papers, match evidence to each test, and flag exceptions for the auditor to review. Every result links back to its source document.
Compliance question answering
Answer questions using approved policies and procedures, with citations linking every answer to its source.
Operations agents with approval steps
Support repeated finance processes while keeping a person responsible for sensitive or high-risk decisions.
Every system can show its work
An invoice agent reads the document, extracts the relevant fields and checks them against the ledger and your policy.
When the evidence is incomplete, the values do not match or the system is uncertain, it stops and sends the case to a person.
Every action, source and decision is recorded.
One escalation path. One audit trail. One definition of correct.
How we handle your data
- Your data stays in your environment, in your cloud or on your own servers, unless you agree otherwise in writing.
- We do not use your data to train models, and we use model providers’ no-training and no-retention terms where they are available.
- Only the named people on your project have access, through your own access controls.
- Every action the system takes is logged. Sensitive steps such as postings and payments need a person’s approval.
- At the end of the project, any data we hold is returned or deleted.
Rules differ by country and regulator. Before work starts we review the outsourcing and data-residency rules that apply to you, together with your compliance team.
Who leads this work
Aneeq Khatri
Co-founder & CEO
This work is led by Aneeq Khatri. He started his career in accounting operations and now builds production multi-agent AI systems.
Bring one month-end problem
Spend 30 minutes with a founder who has worked in accounts and builds AI agents.