
Andera is an AI-native platform that automates internal audit and compliance control testing for enterprises.
Andera's Audit AI Platform automates end-to-end control testing for internal audit teams and public accounting firms. The system ingests financial evidence from spreadsheets, PDFs, screenshots, and journal entries, then uses large language models and agentic retrieval to render audit judgments.
The platform covers SOX, operational, and compliance controls, automating evidence requests, discrepancy flagging, and workpaper generation in Excel formats auditors already use. Andera says the system can reduce SOX testing time and cost by up to 75 percent.
Internal audit has seen little meaningful innovation since Sarbanes-Oxley passed in 2002, leaving a large market for automation. Public companies spend an average of $3 million annually on audit fees, with Fortune 100 firms paying upwards of $20 million, creating strong cost pressure.
Large language models and agentic tool use now make it possible to automate judgment-heavy control testing, while CFOs are demanding 200-300 percent efficiency gains from back-office functions. This combination creates a significant opportunity for AI-native audit platforms like Andera.
Andera is AI-native, using proprietary agentic retrieval and probabilistic beam search to surface relevant evidence across billions of tokens rather than relying on rules-based automation. This allows it to handle messy, multi-format evidence and judgment-based controls that earlier tools could not automate.
The company pairs engineers with career auditors, including former Deloitte and Revolut accounting leaders, to build workflows that match how auditors actually work. Andera also states that no customer data is used to train models or sent to third-party providers, addressing Fortune 100 security concerns.