RPA Replacement in Finance Ops
AP invoice automation and cost anomaly detection. Every approval checked against exact graph facts — vendor, contract clause, policy — and written as a signed workflow trace, not a brittle screen-scraping bot.
"Your AP team re-keys the same vendor and PO data your RPA bots break on every ERP upgrade, and your cloud bill grew 40% last year with nobody able to explain which product or team drove it. Vouchstone builds one graph of vendors, invoices, contracts, and approval policy — invoice matching and cost-anomaly detection both run off it."
What you are actually dealing with
- RPA bots for AP matching break every ERP upgrade cycle — brittle screen-scraping, not graph-grounded logic
- Invoice-to-PO-to-contract matching is manual whenever the automation breaks, and nobody trusts the exception queue
- Cloud spend growing 30–50% annually with no clear attribution to business outcomes
- Engineering over-provisions "just in case" — 60% of compute is idle or underutilized
- Tagging is inconsistent — cost allocation reports are unreliable
- Finance ops is a handful of people tracking spend and approvals across spreadsheets and a brittle bot fleet
How we ship it
- AP graph: Vendor, Invoice, PurchaseOrder, Contract/ContractClause, and ApprovalPolicy as typed nodes — every match is a deterministic graph fact, not a screen-scrape
- Invoice-to-PO-to-contract-clause matching runs off the graph, with vendor entity resolution flagged for human review before it's ever auto-promoted
- Every approval run is written after the fact as a signed workflow trace — audit evidence and the training signal for the next invoice
- Cost context graph: maps every resource to team, product, feature, and business outcome — not just tags
- AI agents continuously scan utilization, recommend right-sizing, and auto-execute approved changes
- Automated commitment management: RI/SP coverage optimized weekly with approval gates
- Tag enforcement agents: detect untagged resources, auto-tag from deployment metadata, block non-compliant launches
- Unit economics dashboards: cost-per-customer, cost-per-transaction, cost-per-feature — not just cost-per-service
- Anomaly detection agents alert on spend spikes within hours, not at month-end
What we owe you when we miss
Most SI contracts only penalise you for falling behind on payment. Our Reverse SLA flips that - when we miss a named milestone, parity threshold, or budget band, we owe you in credits or refund.
Savings
Named savings target (typically 25–40%) — shortfall refunds proportionally
Visibility
Unit economics dashboard live within 4 weeks of setup or that month is on us
Accuracy
95%+ cost attribution accuracy — every dollar mapped to team, product, or feature
Cost Context Graph + FinOps Operating Model
Cost context graph mapping resources to business outcomes, cloud cost baseline, optimization actions taken with before/after proof, unit economics dashboard, commitment coverage report, and a governance framework for ongoing cost control.
Big SI playbook vs. Vouchstone
One-time cost assessment PDF, 8 weeks, $200K+ — savings recommendations go stale in 30 days
Continuous optimization agents live in 4 weeks, cost context graph, real-time unit economics, Reverse SLA on savings target
Domains your audit + compliance teams care about
Every action signed to the ledger; every signed action chained into a regulator-ready evidence pack matched to the framework controls below. One-click export, OCSF-formatted for your SIEM.
Ready to start?
Five-minute intake. Sixty-second response with a named lead, a draft scope, and a price band. No sales call needed before you see what we propose.
Other flagship engagements
Internal Knowledge Copilots
Narrow, team-specific copilots grounded in tribal knowledge — not one generalist bot that knows a little about everything. Built on a living context graph of your docs, code, contracts, and conversations.
Legacy, ERP & Data-Warehouse Migration
Specialist agents grounded in a knowledge graph of source and target schemas do mapping, CDC pipeline building, and UDF conversion deterministically — COBOL, ASP.NET, Oracle, mainframes, and warehouses migrated with row-level parity proofs.
Compliance & Audit Evidence Automation
SOC 2 evidence collection, PII classification scanning. Controls mapped to policies; every audit run is signed and traceable back to source.