Forest vs Porters (2026)

The platform reads and writes directly to the customer's databases and APIs with no copy layer, with automatic schema introspection across Postgres, MongoDB, BigQuery, Snowflake and REST or GraphQL APIs. SDKs in any language handle coded actions and custom logic.

Workflows run on top of KYC and screening providers such as Sumsub, Onfido, Veriff, Persona and Trulioo, with every provider call recorded. An MCP client consumes any data source, and standard and custom MCP connectors come on every plan.

Agents take authenticated action in outside systems through record level actions and workflow steps, and the SDK adds custom tools.

SourceForest, forest.app and forest.app/pricingread 2026-09-06

The pipeline's output stage acts on what it reads. It triggers banking actions such as account blockage and payments, generates reporting such as third party declarations, sends follow up requests to third parties on auto pilot, and exposes case information directly to end users. Porters names no core banking system, connector, API or integration mechanism and publishes no documentation. It does not say how an account blockage instruction reaches the bank's systems.

SourcePorters, withporters.comread 2026-09-07

Multi step workflows carry approvals, escalation and human in the loop gates, and case inboxes come with dispatch rules, segments and SLAs. Named processes such as KYC and KYB onboarding, regulator information requests, sanctions screening, transaction monitoring and dispute handling run as workflows where agents, automations and humans work the same case. The platform also has a workflow builder, approvals and escalations, LLM steps in workflows and a dispatcher for smart routing and assignment. Workflows are native multi step automation with no external stitching.

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Seizure handling runs through a fixed pipeline of seven stages. They are input, extraction and classification, decisioning, human in the loop, action, result and output. Cases are created, processed and tracked through their lifecycle in a case ledger. Porters runs this pipeline on each case, and its own term for the offering is agentic process outsourcing. Porters names no workflow builder, customer facing runtime, parallel workflow control plane or configuration surface, and a process not in the catalog is added by contacting Porters.

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Automated triggers on time, data and webhook come from the Starter plan. A dispatcher handles smart routing and assignment alongside inbox and case management, and case inboxes carry dispatch rules, segments and SLAs. Intake arrives from a shared inbox, a partner portal or manual entry with deadlines attached, agents call the same workflows through the MCP server, and Forest can be embedded inside Zendesk, n8n and Claude. Work therefore reaches the agent through scheduled, data change and webhook events, an inbound queue with dispatch rules and several inbound channels.

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Work arrives by inbox triage, with incoming documents classified into case types such as seizure, restriction or request for information. The agents process seizures 24/7 and instantly. Follow up requests to third parties go out on auto pilot as steps inside a run. Porters names no schedule, connected system event, webhook or channel beyond document intake.

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Agents ground on the customer's live records. For a regulator request, case context is assembled across CRM, KYC and transaction systems, drafts cite source records, and prior case matching handles repeat questions, all read directly from the customer's own datasources with no copy layer. This context is assembled per run over live operational data. There is no maintained retrieval structure, index, graph or embeddings layer over the customer's knowledge. The data layer is the application's live database.

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Decisioning applies fine tuned automated decisions based on internal risk rules and regulatory requirements, and the processes are built for Pan European regulatory coverage. The customer's rules and the regulatory frame ground each decision, with rules applied per case. Porters describes no maintained retrieval structure over a corpus, and no index, embeddings or queryable store.

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Case and record state persist in the customer's own database as the application's data model, and workflows hold their state across steps. There is no separate memory layer with its own scope and lifetime, and no per user, per team or per workflow memory. Forest does not say how the Forest Assist sidebar keeps session state.

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The system learns continuously from past cases to improve decisioning and actions, by Porters' account. The case ledger is the application's own case record, the system of record for the work itself. Porters names no memory store per customer, per workflow or per agent, and does not say where learned state lives or how a bank removes it.

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High risk actions pause for human approval before they run. Each action's risk and approval requirement is configured, routine actions matching configured patterns can execute without review, and the approval chain is the same for agent initiated and human initiated work. Two person review and per jurisdiction scoping apply to agents, and approvals and escalations come on every plan. Forest runs this review and approve surface itself, enforced at the data layer.

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Human in the loop is a named stage of the pipeline. It sits between decisioning and action, before banking actions such as account blockage or payments are triggered. Porters says automation manages routine work, with humans stepping in only when necessary, so people handle the exceptions. Porters does not say whose humans step in or on what surface. The offering pairs AI with the accuracy of Porters' own Banking Ops experts. Porters names no customer facing review queue, approval surface or way to configure what routes to a human.

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Access control covers basic and advanced RBAC with custom roles, AI agent RBAC with scope and permissions, SSO and SAML from the Starter plan, SCIM provisioning and IP whitelist on Enterprise only, two factor authentication, and external user provisioning for partners and BPOs. Each agent connects under a role defining what it can read and trigger, enforced at the data layer. Forest names SOC 2, HIPAA and GDPR compliance without stating the SOC 2 type or auditor, and its Trust Center at trust.forest.app is a Vanta portal.

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By its own account, Porters is ISO 27001 certified and independently pen tested, and it carries a GDPR compliance badge. Its infrastructure is bank grade, encrypted and monitored at every layer, and customer data is never used to train models. A Vanta trust center sits at app.eu.vanta.com. Porters names no single sign on, SAML, role based access control, SCIM or retention configuration.

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Every agent action gets a record level audit entry recording the model used, the agent's identity, the input data and prompt, the reasoning trace where the model exposes it, tool calls, the action taken and the outcome. Each entry is written at the moment of the action against the record it touched, in the same trail and format as human actions.

Regulator ready exports filter by agent, model, customer or time window and bundle the full action and reasoning trail, and events forward to Drata, Vanta, Sprinto, Secureframe, Datadog, Splunk or a warehouse by webhook or sync. AI agent audit trails and unlimited audit log retention come on every plan, with decision trace reasoning logs from Professional. Forest keeps this runtime trail itself, so a team can reconstruct why an agent acted.

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Cases are created, processed and tracked through their lifecycle in a case ledger, and the platform generates reporting such as third party declarations. Porters names a 24/7 audit trail as a standing part of its regulatory alignment. The ledger records what happened to each case. Porters describes no way to reconstruct the agent's own run, such as which rules fired in decisioning, why a case routed to a human or what the model saw. It describes no surface, export or retention for the audit trail.

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Forest hosts its UI and runs a backend on the customer's own infrastructure that reads and writes the datasources directly, so data never leaves the customer's environment. Every plan, including the free Sandbox, comes with a self hosted Forest Agent. The backend, business logic, permissions and audit trail are deployed in the customer's infrastructure, client hosted, and audit logs and decision traces stay in the customer's environment rather than the vendor's. The vendor hosted UI is a control surface and does not change where the data resides, and no region is given for it.

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Hosting is in the EU or Switzerland and GDPR compliant. Porters gives this as its data privacy default, alongside its commitment that customer data is never used to train models. No region selection or deployment guide is published, and Porters does not say which of the two jurisdictions holds a given customer's data.

SourcePorters, withporters.comread 2026-09-07

Named process workflows cover KYC and KYB onboarding, regulator information requests, sanctions screening, transaction monitoring and dispute handling, each a configurable workflow on top of the providers the customer already uses.

After mapping the customer's ecosystem, Forest's forward deployment team designs three to four workflows with the customer and takes them live over twelve weeks. These are patterns the customer assembles with Forest. There is no template library, catalog of adoptable agents or set of packaged agents.

Forest's ecosystem also has an AI Agents listing of third party agents, such as Sphinx, Diligent.ai and Rulebase, that run under Forest's governance.

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Three complete agentic processes are on offer for a customer to select among. Account seizure processing covers private and public seizures end to end. Insolvency management covers the full lifecycle, from reception over coordination to resolution. Chargeback resolution covers data collection, triage of dispute claims and resolution. Each runs on its own, and processes not listed are built on request as custom work. Porters offers all three as shipped processes. The delivery model is an outsourcing engagement, not self serve adoption.

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The customer brings Claude, GPT or open source models, can switch providers without changing the audit shape or permission model, and has the model name recorded with each action. Anthropic, OpenAI, Mistral and Google Gemini power Forest Assist and the customer's agents, and bring your own model is part of what Forest calls open abstraction. Inference runs against the model the customer approves.

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No model provider is named, and Porters names no customer or admin choice of model or routing. Its commitment that customer data is never used to train models covers data use and does not say whose models run. Its fine tuned automated decisions describe Porters adapting its own stack.

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Every plan includes API access for configuration and data, native SDK support (Node.js, Rails and others) for the self hosted Forest backend, and an MCP Server that exposes Forest to AI agents. The MCP server exposes data, schemas, actions and workflows to any authorized runtime, from Claude to open source models or custom built agents, so Claude and other agents can call Forest under the customer's governance. It runs inbound, letting an outside caller drive the platform, while a separate MCP client consumes outside data sources.

SourceForest, forest.app/pricing, forest.app and forest.app/blog/here-comes-the-new-forestread 2026-09-06

No API, SDK or MCP server for calling the platform from outside is published, and Porters has no developer section or documentation site. The one outward facing behavior it names, exposing case information directly to end users, serves end users and gives no way to drive Porters.

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Workflow analytics and optimization come from the Professional plan, giving a team a live metric on operations to read when tuning a workflow, and the decision trace reasoning log lets a reviewer see how an agent reached a decision after the fact. Forest offers no evaluation harness, scored test cases, release gate or controlled loop for measuring a change to the agent. It says it does not evaluate model output for accuracy or run safety tests, and it points customers to upstream tools.

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Built in accuracy validates consistent business logic instantly within the workflow, gating each output as it is produced. That checks each output as it is made, and Porters describes no way to test a change. The system is said to learn continuously from past cases to improve decisioning, but Porters describes no harness, test set, scored result or controlled loop behind that claim. No readable result or release gate is published.

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Forest's own agents and workflow steps reach outside systems through direct database access, APIs and MCP connectors, and the platform drives no browser, desktop or computer control. The ecosystem lists Sphinx, a partner's browser native agent that logs into compliance tools like an analyst. Sphinx is an outside agent that calls Forest under its governance.

SourceForest, forest.app/platform/ai-governance-llm-ops and forest.appread 2026-09-06

The agents work on documents that arrive in inboxes and act through banking instructions and generated reports. They take in unstructured documents, which Porters says they handle with ease. Porters describes no browser, desktop or computer control by the agents.

SourcePorters, withporters.comread 2026-09-07