Finance is the investment flywheel that propels a business forward. Finance teams use Dough to build, deploy and govern AI agents from Claude or Codex.
e.g. Agent prepares the weekly Treasury cash forecast using current payment data and liquidity projections, flags key variances, refreshes stale assumptions, and produces a submission-ready narrative.
e.g. Agent reconciles merchant proceeds in transit, prepares journal entries and aging files, reviews clearing accounts, and supports receivable write-off analysis across close subtasks.
e.g. Agent reviews pending Coupa requisitions, purchase orders, change orders, and invoices against budget and committed spend, then recommends approve, return, or discuss outcomes with draft approver comments.
e.g. Agent reviews 10-Q and 10-K shells in Workiva by checking roll-forward completeness, financial statement footing, prior-period tracing, stale language, cross-references, and required disclosure consistency.
e.g. Agent pre-reviews audit memos against historical drafts, prior comment patterns, and auditor-question themes to anticipate likely review comments while preserving human review.
e.g. Agent automates commission-cycle calculations by deriving target achievement percentages and representative payout amounts for sales operations review.
e.g. Agent performs gross-to-net payroll reconciliation across Workday and other systems to identify variances in gross pay, deductions, taxes, and net disbursements before close.
e.g. Agent produces a monthly SG&A variance report from NetSuite, Anaplan, and DataMart data, with planning-unit context and employee- and vendor-level drilldowns.
e.g. Agent builds a quarterly growth investment view covering revenue health, ROI by tenure cohort, rep-level indicators, market metrics, and hiring recommendations.
e.g. Agent supports quarterly KPI planning by recommending measurable KPIs, evaluating proposed targets, and calculating achievement at period end for department, vertical, and team leaders.
e.g. Agent processes non-standard payment-term deal requests by querying BigQuery, applying finance rules, returning approve/reject/escalate decisions with an audit trail, and logging exceptions for follow-up.
Your agents are intelligently routed through one shared context layer: a normalized data lake, direct API connections, and a shared file system. No more exploding your context window with multiple inefficient MCPs.
Build an agent once and share it with a single click. Agents and skills live in a versioned repository that is multi-skill, reusable, and governed, instead of scattered across laptops and one-off prompts.
Measure agent efficacy, not vibes. Built-in evals score every agent against your standards, so your team can iterate with confidence and show improvement over time.
See what every agent actually costs. Token spend is tracked per run and tied to ROI, with no vendor token markup and no guessing where your spend goes.
Every agent run, session, MCP call, and tool call is logged, capturing the full reasoning chain behind each output, audit-ready by default.
SOX controls built in, with ICFR card workflows, segregation of duties, plus OAuth and credential management that close the gaps horizontal tools leave open.
Run hosted agents on schedules with durable execution. Remove the laptop from the equation and have agents monitor inboxes and close loops on your behalf in our governed environment.
Granular, configuration-driven access control. Data is scoped by role and department, so each person sees only what they should, keeping sensitive data governed end to end.
See how Dough delivers governance automatically for an agent reviewing purchase orders in an enterprise environment.
Each PO the agent reviews lands in a full session log, and runs can be used for evals automatically. The back and forth between your team and the agent is logged. The approvals are logged. Your audit trail writes itself.
RBAC scopes agents to operate on-behalf-of users in platforms like Slack and only disclose data that users are allowed to access. API keys are stored in encrypted vaults not users' laptops. Controls are enforced by the platform, not left to the agent.
The run pulls the current Procurement Agent from the shared repo, not a stale copy on someone's laptop. Agents have skill versions pinned to them and they are only updated when the team approves.
Agents are given the best path to access the data they need. In this case, the agent uses API keys to query outstanding POs (Coupa), data lake snapshot tables to query the latest budget (Anaplan) and a file system to access any ad-hoc changes. No inefficient MCPs exploding the context window.
You own the agents and the IP either way.
