Reconciliations, onboarding packets, and reporting cycles consume analyst hours your firm can't bill for. We design automation your compliance team can approve — auditable, private, integrated with your core systems — and then we engineer it ourselves. One team from roadmap to production.
Every month, capable analysts rekey statement data, chase unmatched transactions, and rebuild the same reports — work that is procedural, error-prone, and invisible to clients. Because the steps are manual, they are also the weakest links in your control environment: the places where mistakes slip through and findings originate.
We automate the procedural layer and leave the judgment where it belongs — with your people, inside a workflow your auditors can trace end to end.
Where AI Helps First
Matching, GL mapping, and tie-outs are where analysts lose their month. Automation compresses the close and turns rekeying mistakes into flagged exceptions a human reviews.
Statements, subscription docs, tax forms, KYC packets — extraction that reads them the way an analyst would, with a person approving the output before it moves downstream.
Recurring reports assembled from source data on schedule, with every figure traceable back to where it came from. The auditability matters as much as the speed.
What We Do
We chart which back-office functions — client onboarding, reconciliation, regulatory reporting — justify automation, with the model-risk and audit questions answered up front rather than after your compliance team objects.
A structured walkthrough of your close calendar, KYC pipeline, and document queues, scoring each workflow on hours saved, error exposure, and how cleanly it can be audited.
Document extraction, GL mapping, exception-flagging reconciliation — engineered against the platforms your firm runs, whether that's Salesforce Financial Services Cloud, NetSuite, or a core banking stack, and owned by you at handoff.
Deployments where client records never leave your environment and every automated decision leaves a trail an examiner can follow. Nothing trains a public model, and your vendor-review process gets the documentation it expects.
Proven Result
A private-equity-backed client came to us with a ledger-mapping process that swallowed days of skilled finance time every cycle. We rebuilt it so the machine does the mapping and an analyst signs off. Real financial data, real controls — that engagement is the template for how we approach back-office automation, built on enterprise AI experience earned inside a Fortune 50 company.
See customer resultsFAQ
In this industry the job is half engineering, half governance. We identify the manual work — onboarding packets, reconciliations, reporting cycles — that automation can absorb, then design each system so model risk, access control, and audit trail are settled before build starts. HummingAgent handles both the advisory and the engineering, so the roadmap and the deployed system come from the same team.
For one private-equity-backed client we rebuilt a general-ledger mapping process that had consumed multiple days of skilled time each cycle; it now runs as an automated pass followed by a short human review. We know what a chart of accounts looks like, what breaks a reconciliation, and which controls your auditors will ask about.
Start where documents pile up and the judgment is procedural: extracting data from statements and KYC files, mapping and matching inside the reconciliation process, and assembling recurring regulatory or board reporting. None of these touch credit or investment decisions, which keeps model-risk review straightforward and approvals faster.
Every workflow we ship logs its inputs, its outputs, and the human approvals in between, so an internal auditor or examiner can reconstruct any decision. Client data stays inside your environment — private deployment, no public-model training — and we document the system in the format your model-risk or vendor-review process expects to receive.
Pricing follows scope, and scope in financial services is driven by controls: a document-extraction workflow with a human approval step is a smaller build than one that writes to your general ledger. Discovery produces a fixed audit fee; build work is quoted project by project. Our AI pricing guide publishes typical ranges.
The pacing question in this industry is usually compliance review, not engineering. Once your risk team clears the data-handling design, we begin with one bounded workflow — a single document type or a single reconciliation — which validates the business case before anything expands across the back office.
In one call we'll walk through your close, onboarding, and reporting workflows, estimate the hours at stake, and describe a build your compliance team could sign off on.
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