Adaptive delivers AI-powered accounting automation tailored for the construction industry. The company develops Project Accounting Agents that automate day-to-day accounting workflows, addressing workflows specific to construction finance where project-based accounting creates unique compliance and operational challenges. Adaptive's approach combines agentic AI reasoning with auditability—critical for regulated financial environments.
Researchers identify how deep research agents' adaptive search strategies create selective sampling of evidence, risking misleading audit conclusions even when citations are technically correct.
CLAIR-Fin, a nine-agent framework, verifies financial claims at the atomic level using a typed ledger and cross-modal debate to prevent hallucinations in retrieval-augmented financial QA systems.
Researchers propose DRQN-CMDP, a deep reinforcement learning approach using recurrent neural networks to adaptively schedule audits of off-chain data while maintaining security miss-rate constraint...
VADAOrchestra combines LLM-based agentic reasoning with symbolic logic to enable adaptive, auditable decision-making in business processes—addressing a core tension in AI-driven accounting workflows.
VADAOrchestra combines symbolic logic with LLM-based reasoning to enable adaptive business workflows that maintain auditability—addressing a key gap for regulated industries like accounting and fin...
Adaptive debuts Project Accounting Agents to automate day-to-day accounting tasks in construction finance, addressing a niche but critical workflow gap.
Researchers propose AuditFlow, a graph-grounded multi-agent AI system that automates financial audit verification by linking reported facts to taxonomy concepts and recomputing values against audit...
Production study demonstrates HOPM framework for auditable, evidence-grounded document generation in marketplace disputes—bridging AI reliability with accounting/compliance audit trails.
Academic paper proposes anytime-valid statistical guarantees for adaptive auditing of generative AI systems, addressing the bottleneck of costly manual annotation in characterizing AI failure modes.
Researchers propose an explainable ensemble learning approach using Shapley values to detect financial fraud while meeting OCC and Federal Reserve transparency requirements, addressing $32B annual ...