Esker is expanding its AI strategy for the Office of the CFO with the launch of the Synergy Agentic Framework, a governed agentic layer designed to coordinate AI-driven execution across Source-to-Pay and Order-to-Cash processes.
Built on Esker’s existing Synergy AI capabilities and transactional platform, the framework combines specialized Business Agents, conversational interactions, enterprise connectivity and human-defined governance. The aim is to move finance automation beyond individual tasks toward broader sequences of work, while retaining controls around permissions, policies, approvals and higher-risk decisions.
The launch reflects a wider shift taking place across enterprise finance. As organizations explore agentic AI for processes involving invoices, payments, collections, credit and customer operations, greater autonomy also increases the importance of governance, attribution and auditability. Esker’s approach is to place agentic capabilities within the existing context of finance workflows rather than treating agents as standalone automation tools.
Moving From Task Automation to Agentic Finance Workflows
Esker has already embedded AI into finance processes including document recognition, data extraction, matching, anomaly detection, auto-coding and prioritization.
The Synergy Agentic Framework adds reasoning, orchestration and greater autonomy to that foundation. Business Agents are designed to perform repetitive activities across Source-to-Pay and Order-to-Cash while escalating situations requiring human judgment.
Potential activities include identifying invoice exceptions, routing approvals, prioritizing collections, assessing credit risk, supporting cash application, resolving claims and helping customer service teams respond to inquiries.
“Finance leaders are seeking trusted solutions that can coordinate work across functions while preserving control, rather than a disconnected suite of AI tools,” said Eric Bussy, Chief Marketing Officer and Head of Product Management at Esker. “With the Synergy Agentic Framework, Esker is helping the Office of the CFO do just that: use AI as a governed extension of their finance team, from automating tasks to fully orchestrated agentic workflows that support decision-making.”
The framework builds on existing Esker automation deployments, where the company says customers have reported more than 90% touchless invoice processing, reductions in DSO of over 40%, and more than 3x faster approvals, dispute resolution and order processing.
Rather than presenting these existing automation results as outcomes of the new framework, Esker positions the Synergy Agentic Framework as the next step: extending automation from individual tasks toward connected sequences of governed execution.
Act, Talk and Connect
Esker has structured the framework around three core capabilities: Act, Talk and Connect, supported by common foundations for context, intelligence, control and assurance.
The Act component focuses on autonomous execution. Business Agents combine Synergy AI models and predictions with established business rules, workflows and actions. Routine work can be handled by agents, while decisions outside predefined boundaries or requiring judgment can be escalated to people.
Talk introduces what Esker calls Conversational Finance. Users can express requests in natural language, with the framework connecting those requests to the appropriate context, workflow or Business Agent. The system can retrieve information, guide users through intake processes or carry out a governed action.
The interaction can also work in the opposite direction. The platform can engage users when human approval, clarification or confirmation is necessary—for example, when an invoice requires urgent approval or a receipt against a purchase order needs to be recorded.
The third component, Connect, is intended to make selected finance capabilities available to other people, systems and external AI agents while keeping identity, permissions, business policies and resulting actions governed within Esker.
Connecting Agentic AI With ERP and Enterprise Systems
The framework has also been designed to operate within broader enterprise technology environments rather than as an isolated AI layer.
Through APIs and emerging standards including Model Context Protocol (MCP) and Agent-to-Agent (A2A), Esker says its finance workflows and agents can connect with enterprise AI platforms, large language models, ERP systems and CRM environments.
This interoperability could become increasingly important as organizations build enterprise AI architectures involving multiple platforms and agents. Instead of providing external agents with unrestricted access to finance systems, Esker’s model is designed to expose controlled capabilities while keeping permissions and resulting financial actions within its governance layer.
For ERP environments, this addresses a central question surrounding agentic AI: how to allow intelligent systems to interact with core enterprise processes without bypassing the business rules and controls already governing those processes.
“The value of an AI agent does not come from the model alone,” said Jean-Jacques Bérard, Chief Product and Technology Officer at Esker. “It comes from combining the right intelligence with trusted transaction context, business rules, and governed execution.”
BĂ©rard added that the framework is intended to coordinate work across Source-to-Pay and Order-to-Cash processes and different systems while keeping finance leaders in control.
Combining Probabilistic AI With Deterministic Execution
One of the more significant elements of Esker’s approach is the distinction between AI reasoning and financial execution.
Generative and agentic AI systems are probabilistic by nature, while financial transactions generally require predictable execution, defined authorization boundaries and traceable outcomes.
Esker says the Synergy Agentic Framework addresses this by anchoring AI reasoning in its transactional platform. Workflows, business rules, permissions, validations and audit trails determine how approved actions are ultimately executed.
The framework also draws on Esker’s Data Lake and Benchmark Intelligence. KPIs, historical performance information and anonymized peer benchmarks can be used to identify performance gaps and measure results, with those insights feeding back into both agentic execution and human decision-making.
This combination of adaptable AI reasoning and controlled transaction execution is particularly relevant as finance departments consider allowing agents to move beyond recommendations and perform actions that affect operational or financial records.
Governance Becomes Central to Finance AI
Esker describes the longer-term direction behind the framework as Governed Autonomous Finance—an operating model in which AI performs more execution while people retain authority over objectives, policies, exceptions and higher-risk decisions.
The concept reflects a broader evolution in enterprise AI. Early deployments have largely focused on assisting employees with discrete tasks. Agentic systems introduce a different model in which AI can potentially coordinate multiple steps, interact with other systems and initiate actions.
That transition raises the stakes for the Office of the CFO. Finance processes operate across sensitive data, business-critical transactions and tightly controlled approval structures, making unrestricted autonomy difficult to reconcile with enterprise governance requirements.
Esker’s Synergy Agentic Framework represents an effort to bridge those two requirements: increasing the amount of work AI can execute while maintaining human-defined boundaries around how, when and where agents can act.
As agentic AI moves deeper into ERP-connected finance operations, this balance between autonomy and deterministic control is likely to become a defining issue. The next stage of finance automation will therefore be shaped not simply by how capable AI agents become, but by how effectively enterprises can connect those capabilities to trusted transaction context, established business rules and accountable human oversight.
ERP News Editorial Team
The ERPNews Editorial Team covers global developments in ERP (Enterprise Resource Planning), enterprise software, cloud platforms, AI, automation, and digital transformation, providing independent news and editorial analysis for senior business and technology leaders. Our reporting focuses on market signals, strategic shifts, and enterprise impact across the ERP and enterprise technology ecosystem.
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