{"@context":"https://schema.org","@type":"FAQPage","mainEntity":[{"@type":"Question","name":"What is agentic ops?","acceptedAnswer":{"@type":"Answer","text":"Agentic ops is a category of business operations where AI agents autonomously execute multi-step workflows against live systems of record, reasoning about goals, handling exceptions, and escalating to humans when policy limits are reached. It replaces the manual-review layer that RPA and rules engines never reached."}},{"@type":"Question","name":"What is the difference between agentic AI and agentic ops?","acceptedAnswer":{"@type":"Answer","text":"Agentic AI refers to the AI agent itself: the model plus its capacity to plan, use tools, and act. Agentic ops is the operating model that puts agentic AI to work on real business workflows, with the surrounding infrastructure for data access, permissions, audit, and human escalation. Agentic AI is the engine. Agentic ops is the vehicle."}},{"@type":"Question","name":"How is agentic ops different from RPA?","acceptedAnswer":{"@type":"Answer","text":"RPA (robotic process automation) follows fixed scripts and breaks on exceptions. Agentic ops uses AI agents that reason about the goal, adapt to new situations, and handle exceptions. RPA is deterministic. Agentic ops is contextual."}},{"@type":"Question","name":"How is agentic ops different from AI automation?","acceptedAnswer":{"@type":"Answer","text":"Automation follows fixed rules and breaks on exceptions. Agentic ops uses AI agents that reason about the goal, handle exceptions as they arise, and escalate to humans when judgment is required. Every action is logged at the record level."}},{"@type":"Question","name":"When did agentic ops emerge as a category?","acceptedAnswer":{"@type":"Answer","text":"The term crystallised in 2025 as Model Context Protocol, released by Anthropic in late 2024, gave AI agents a standard way to reach real business tools. Before that, deploying AI agents in operations meant custom glue for every workflow. Forest is the first infrastructure built specifically for agentic ops in regulated fintech."}},{"@type":"Question","name":"Which fintech workflows can AI agents already run?","acceptedAnswer":{"@type":"Answer","text":"KYC review, dispute handling, transaction monitoring, and onboarding exceptions. AI agents pull identity data, cross-reference watchlists, triage disputes, apply risk scoring, draft SARs, and escalate edge cases to your team with full context attached."}},{"@type":"Question","name":"Why is agentic ops harder in fintech?","acceptedAnswer":{"@type":"Answer","text":"Every action needs to be explainable to a regulator. Data can't leave your environment. Permissions need to distinguish what your team can do from what your AI agents can. When something goes wrong, your team needs a complete record of every decision that led there."}},{"@type":"Question","name":"What does agentic ops done right look like in fintech?","acceptedAnswer":{"@type":"Answer","text":"AI agents that operate inside your compliance framework, not around it. A full audit log covering humans and AI agents in the same record. Permissions set at the action, workflow, and record level. A human escalation path your team can actually use."}},{"@type":"Question","name":"Does agentic ops replace human ops teams?","acceptedAnswer":{"@type":"Answer","text":"No. Agentic ops keeps humans in the loop for exceptions and judgment calls. AI agents handle the routine work, gather context on edge cases, and escalate to your team when policy limits are reached or ambiguity is high. Your team spends time on the decisions that actually need judgment."}},{"@type":"Question","name":"What is Model Context Protocol (MCP)?","acceptedAnswer":{"@type":"Answer","text":"Model Context Protocol is the open standard, released by Anthropic in late 2024, for how AI agents connect to tools and data. Forest exposes your data and tools through the Forest MCP Server, which any MCP-compatible AI agent can call under the same permissions and audit coverage as your team."}}]}