PLATFORM

Enterprise AI Agent Integrations

Your enterprise apps hold the data. MightyBot connects AI agents to systems of record, executes the decisions, and writes results back through native connectors, REST, GraphQL, and webhooks. Work finishes in the systems you already run, which is where productivity shows up.

Why MightyBot

MightyBot connects AI agents to the systems where work actually happens: LOS, CRM, ERP, databases, warehouses, Google Workspace, Slack, and anything with an API. Agents read from systems of record, execute decisions, and write results back through native connectors, REST, GraphQL, and webhooks.

How Enterprise AI Agent Integrations Work

An underwriting decision needs borrower data from Salesforce, documents from the LOS, and policy rules from your compliance system. MightyBot pulls all of it, executes the evaluation, and writes the result back to every system that needs it.

Bidirectional by default. Your LOS stays the system of record. Your CRM stays the relationship hub. MightyBot adds the execution layer that connects them.

Connected context makes agents smarter.

Native Integrations for Systems of Record

Pre-built, maintained connectors for the platforms your teams use daily.

A system of record holds the authoritative data (the loan file, the policy, the ledger). A system of action is where a decision gets executed (the approval posted, the exception routed, the document filed). AI agents are only useful in production when they can read the first and write to the second, with every write logged.

Systems of Record
LOSCRMERP
Bidirectional sync of application, borrower, opportunity, and account data. Agents pull context, execute policy evaluations, and push results back. No manual data entry.
Productivity & Communication
EmailFile StorageMessagingVideoImage FeedsTicketing
Google Workspace: Gmail, Drive, Calendar, Meet. Slack: notifications, approvals, and status updates in existing channels.
Databases & Data Warehouses
SQLS3SnowflakeIceberg
Direct connections to SQL databases, S3, Snowflake, and Iceberg. Compliance exports land directly in your data warehouse. Decision records flow to your analytics infrastructure automatically.

Each native integration maintained by MightyBot's engineering team. API updates. Authentication changes. Schema migrations. You do not maintain integration code.

Integration inventory

  • LOS and lending platformsLOS
  • CRMCRM, Salesforce
  • ERP and financeERP
  • Data warehouses and databasesSQL, S3, Snowflake, Iceberg
  • CollaborationGoogle Workspace, Slack
  • Custom systemsREST, GraphQL, webhooks

Integration patterns

  1. Native connector
  2. REST or GraphQL API
  3. Webhook
  4. Event trigger

API-First Execution

For systems without native connectors, standard protocols connect anything.

REST and GraphQL

Any system with a REST or GraphQL interface connects to MightyBot. Define authentication, endpoints, schemas, and error handling. Agents interact with external systems as naturally as native integrations.

Webhooks and Event-Driven Triggers

A new loan application fires a webhook. A document upload triggers processing. Inbound webhooks accept JSON payloads and route to the appropriate workflow.

JSON Data Exchange

Standard JSON. No proprietary formats. Standard protocols mean standard debugging, monitoring, and security.

MCP Launchpad: Your Workflows Become Agent-Callable Tools

The assistants, copilots, and coding agents your teams already run can call MightyBot workflows directly, with every call governed by the same policies and evidence trail.

Encoded once
SchemasRulesExamples
A workflow already contains the field schemas, validation rules, and real examples an agent needs to call it correctly. MCP Launchpad generates a fully described, domain-named tool from that workflow context. Generic API-to-MCP wrappers cannot produce the same result.
Governed once
PoliciesEvidence
Every call runs the workflow underneath: the same APIs, the same policies, the same evidence trail. Governance does not loosen because an agent made the call instead of a person.
Called anywhere
AssistantsCopilotsCoding agents
Expose approved workflows to internal assistants, customer-facing copilots, or any MCP-compatible agent your enterprise runs. No rebuilt integration for every surface.

Encoded once. Governed once. Callable wherever the work happens.

How It Works

A commercial loan application end-to-end. No one leaves their existing tools.

01

A commercial loan application is created in your LOS.

02

A webhook fires. The underwriting workflow starts.

03

Agents pull borrower data from Salesforce.

04

Documents are processed by the Data Engine.

05

The Policy Engine evaluates against underwriting policies.

06

Results write back to your LOS.

07

The underwriter gets a Slack notification with a summary and review link.

See your systems become systems of action.

Request a demo

Explore the stack

The rest of the Decision Execution Stack.

Agent CompilerFrom plain English to working agent. No canvas, no flowcharts: describe the work and the platform compiles the execution plan.ControlPolicy EnginePlain-English policies compiled into deterministic execution paths.RuntimeCompiled Agent ExecutionParallel execution plans for regulated workflows instead of sequential prompt chains.EvidenceData EngineDocument intelligence, canonical extraction, and source evidence pointers.AuditCompliance InfrastructureWhy-trails, review gates, evidence records, and examiner-ready exports.SecuritySecure AI Agent PlatformSOC 2 Type II controls, tenant isolation, encryption, and access governance.Measured evidenceAgent Evaluation Cost StudyMeasured token costs of single-pass, agentic, and voting configurations on the same workload.

FAQ

Frequently Asked Questions

Can AI agents write back to systems of record?

Yes, through native connectors, REST, GraphQL, and webhooks. Every write-back is policy-gated and logged with the decision that produced it, so the system of record stays authoritative and auditable.

What is a system of action for AI agents?

The system where an agent's decision takes effect: a loan origination system that receives the underwriting result, a CRM that gets the follow-up, a ticketing system that opens the exception. MightyBot treats write-back to systems of action as part of the workflow, not an afterthought.

Which enterprise systems can MightyBot AI agents integrate with?

Any system with a REST API, GraphQL endpoint, webhook support, or native connector. MightyBot connects to LOS, CRM, ERP, databases, warehouses, file storage, communication tools, and proprietary systems.

Does MightyBot support bidirectional sync with Salesforce?

Yes. Agents pull borrower and opportunity data. Decision results and status updates push back to relevant records. Bidirectional by default.

How are API credentials and authentication handled?

OAuth2 for enterprise integrations. JWT for service-to-service. API keys for multi-tenant access. Credentials encrypted at rest and in transit.

What happens if an external system is temporarily unavailable?

Configurable retry policies and fallback behavior. Workflows pause and resume when connectivity restores. Full state maintained. No lost work.

Do we need custom code to integrate?

No custom code for native connectors or standard REST/GraphQL APIs. Configuration through MightyBot's interface - endpoint, authentication, data mapping, error handling.

Can our own AI assistants and copilots call MightyBot workflows?

Yes. MCP Launchpad exposes approved workflows as agent-callable MCP tools. The tool description is generated from the workflow itself (schemas, rules, and real examples), and every call runs through the same policies and evidence trail as the workflow underneath.

Can MightyBot trigger workflows from events in our existing systems?

Yes. Inbound webhooks accept JSON payloads from any HTTP-capable system. Applications, uploads, status changes - all valid triggers.

Last updated: August 6, 2026