Moving finance in-house introduced complex multi-entity allocations. The team now builds custom AI agents to automate these workflows.
A rapidly scaling device-aware artificial intelligence company transitioning its financial operations from an outsourced accounting firm using QuickBooks to an internal team using NetSuite.
As operational complexity and international expansion increased, the new internal finance team needed to manage intricate intercompany allocations...
“I wanted to avoid a hodgepodge of random systems and connections everywhere. At previous companies, I have seen accelerated growth in the business put Finance on their back heel, leading to a bunch of bandaid solutions or disparate systems that didn't talk well together.”
Efficient foundation models and deployment platforms for edge and enterprise AI.
Accounting workflow automation platform for financial close management.
Related implementations across industries and use cases
Accountants manually scoured mailboxes to assemble 15 subsidiary workbooks. Now, staff-built AI agents pull invoice data for instant review.
Doubled patient revenue bottlenecked manual Excel reconciliations. Now, AI matches complex transactions, freeing accountants for strategy.
Ambiguous data forced manual review. Now, a GPT-5 supervisor routes tasks to sub-agents and surfaces assumptions for verification.
Mapping workflow logic once took weeks. Now, users build autonomous Claude agents in minutes to reason through multi-step tasks.
Static spreadsheets bottlenecked approvals. Now, non-technical staff use AI to build guided, interactive workflows in minutes.
Scattered spreadsheets couldn't catch AI hallucinations. Now, automated LLM judges evaluate every prompt change to block regressions.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Auditors lost hours manually recalculating financial statements. Now, AI verifies math and consistency so teams can analyze exceptions.
Manual journal entry testing took three days. Automated document matching cuts this to hours, freeing auditors for advisory work.
Moving finance in-house introduced complex multi-entity allocations. The team now builds custom AI agents to automate these workflows.
A rapidly scaling device-aware artificial intelligence company transitioning its financial operations from an outsourced accounting firm using QuickBooks to an internal team using NetSuite.
As operational complexity and international expansion increased, the new internal finance team needed to manage intricate intercompany allocations...
“I wanted to avoid a hodgepodge of random systems and connections everywhere. At previous companies, I have seen accelerated growth in the business put Finance on their back heel, leading to a bunch of bandaid solutions or disparate systems that didn't talk well together.”
Efficient foundation models and deployment platforms for edge and enterprise AI.
Accounting workflow automation platform for financial close management.
Related implementations across industries and use cases
Accountants manually scoured mailboxes to assemble 15 subsidiary workbooks. Now, staff-built AI agents pull invoice data for instant review.
Doubled patient revenue bottlenecked manual Excel reconciliations. Now, AI matches complex transactions, freeing accountants for strategy.
Ambiguous data forced manual review. Now, a GPT-5 supervisor routes tasks to sub-agents and surfaces assumptions for verification.
Mapping workflow logic once took weeks. Now, users build autonomous Claude agents in minutes to reason through multi-step tasks.
Static spreadsheets bottlenecked approvals. Now, non-technical staff use AI to build guided, interactive workflows in minutes.
Scattered spreadsheets couldn't catch AI hallucinations. Now, automated LLM judges evaluate every prompt change to block regressions.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Auditors lost hours manually recalculating financial statements. Now, AI verifies math and consistency so teams can analyze exceptions.
Manual journal entry testing took three days. Automated document matching cuts this to hours, freeing auditors for advisory work.