INVITING AI AGENTS IN

Welcome AI agents into your ops. Keep your auditors calm.

Welcome AI agents into your ops. Keep your auditors calm.

Welcome AI agents into your ops. Keep your auditors calm.

Giving AI agents safe access to your operations is more an infrastructure problem than a model problem. Here's what your stack needs in place first.

THE REAL BLOCKER

Most regulated companies have the AI capability they need. The infrastructure for AI agents to operate safely is where the gap is.

Most regulated companies have the AI capability they need. The infrastructure for AI agents to operate safely is where the gap is.

Deploying AI agents in regulated operations is more an infrastructure problem than a model problem. The models are capable. The use cases are clear. Yet 88% of AI agent pilots never reach production (IDC, 2026). What stops most regulated companies from moving faster is ops readiness, not AI readiness. Your AI agents need live access to your data, scoped permissions, a way to escalate to humans, and a full audit trail on everything they touch. Without that infrastructure, you don't have agentic ops. You have an experiment.

WHAT IT TAKES

Put in place the mechanics required for AI agents to operate safely.

Put in place the mechanics required for AI agents to operate safely.

01

Live data access through Forest's backend

Forest's backend deploys inside your environment. Your AI agents read and write through it directly to your databases and SaaS tools. No ETL, no copy layer, no snapshot.

02

Permissions at the action, workflow, and record level

Your team scopes each AI agent's access to specific actions, workflows, and records. Same RBAC model that governs your team, applied to your AI agents the same way.

03

Configurable human escalation

Your team sets escalation thresholds, by confidence level, by action type, by risk score. Forest routes the right context to the right human at the right moment, with the case history attached.

03

Configurable human escalation

Your team sets escalation thresholds, by confidence level, by action type, by risk score. Forest routes the right context to the right human at the right moment, with the case history attached.

HOW AI AGENTS CONNECT TO YOUR OPS

Your AI agents never touch your systems directly. Forest's backend is what connects them.

Your AI agents never touch your systems directly. Forest's backend is what connects them.

Your AI agents never touch your systems directly. Forest’s backend is what connects them.

Layer
What sits here
What it enforces
Your infrastructure
What sits hereDatabases, CRMs, core banking, PSPs, KYC providers, communications platforms
What it enforcesSystems of record. Data stays here.
Forest backend
What sits hereDatasource connectors, MCP tasks inside workflows, custom actions, Forest MCP Server
What it enforcesScoped permissions, record-level audit, escalation routing
AI agents and human operators
What sits hereAny MCP-compatible AI agent runtime. Your team through the Forest UI.
What it enforcesSame permission model, same audit trail, same record

Customer data travels to a provider only at the point where its service is called, and the response is logged back to the case. Custom actions reach into other resources across your infrastructure. Every AI agent action inherits your team’s permissions model.

Connecting AI agents to your stack

Connecting AI agents to your stack

Connecting AI agents to your stack

Q1

How does Forest plug AI agents into the tools your team already runs?

Forest's backend connects to your datasources: your databases, your SaaS tools, your systems of record. Inside workflows, MCP tasks call your external tools (KYC providers, PSPs, communications platforms, case-management systems). Customer data travels to a provider only at the point where its service is called, and the response is logged back to the case. Custom actions reach into other resources across your infrastructure. The Forest MCP Server opens all of that up to your AI agents, with the same scoped permissions and audit coverage your team works under.

Q2

How does agentic ops governance hold up under a regulator audit?

When a regulator asks what happened, the Forest record shows four things: the instructions each AI agent was given, the data it accessed, the actions it triggered, and the outputs it produced. Permissions are fine-grained: your team gives each AI agent the access it needs for one job and no more, scoped at the action, workflow, and record level. The answer covers humans and AI agents in the same record.

Let us get you started

More on agentic ops adoption in fintech.

More on agentic ops adoption in fintech.

Let's look at your infrastructure together.

Talk to the team. We'll map your current setup and show you exactly what it takes to bring AI agents in safely, and what your team can run on day one.

Let's look at your infrastructure together.

Talk to the team. We'll map your current setup and show you exactly what it takes to bring AI agents in safely, and what your team can run on day one.

Let's look at your infrastructure together.

Talk to the team. We'll map your current setup and show you exactly what it takes to bring AI agents in safely, and what your team can run on day one.

Frequently asked questions

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How do I deploy AI agents in fintech operations?

Give your AI agents live data access through Forest's backend, permissions scoped at the action, workflow, and record level, configurable human escalation, and a full audit trail on everything they touch. Start with one workflow where the use case is clear and the risk is contained. Expand as your team gains confidence and accumulates audit history.

What is Model Context Protocol (MCP)?

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.

Which AI agent frameworks does Forest support?

Any MCP-compatible runtime: Claude, GPT, open-source models, custom AI agents your team has built. Forest is model-agnostic and framework-agnostic.

Can AI agents access customer data on Forest?

The Forest backend runs inside your infrastructure, alongside your databases. Your AI agents read and write through it directly to your databases and SaaS tools. Customer data travels to a provider only at the point where its service is called. Data stays in your systems of record.

How does Forest plug AI agents into the tools your team already runs?

Forest's backend connects to your datasources. Inside workflows, MCP tasks call your external tools (KYC providers, PSPs, communications platforms, case-management systems). Custom actions reach into other resources across your infrastructure. The Forest MCP Server opens all of that up to your AI agents, with the same scoped permissions and audit coverage your team works under.

How does agentic ops governance hold up under a regulator audit?

When a regulator asks what happened, the Forest record shows the instructions each AI agent was given, the data it accessed, the actions it triggered, and the outputs it produced. Permissions are fine-grained: your team gives each AI agent the access it needs for one job and no more. The answer covers humans and AI agents in the same record.

What permissions do AI agents need to run in production?

Scoped access at the action, workflow, and record level. Same RBAC model that governs your team, applied to your AI agents the same way. Your team decides what each AI agent can read, write, or trigger, and Forest enforces it on every call.

Can I use Claude or GPT with Forest?

Yes. Forest works with any MCP-compatible AI agent runtime: Claude, GPT, open-source models, custom AI agents. Plug your own model for the AI inside Forest workflows. Switch as the landscape evolves.

Where does customer data go when AI agents run on Forest?

The Forest backend runs inside your infrastructure, alongside your databases. Customer data travels to a provider only at the point where its service is called, and the response is logged back to the case. Data stays in your systems of record.

How is Forest different from a custom AI agent framework?

Custom frameworks assume you can ship data to an external API, that audit is optional, and that permissions get sorted later. Forest assumes the opposite. Your data stays in your environment. Every AI agent action is logged at the record level. Permissions are scoped before any AI agent connects.

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