The industry default
Most AI platforms bolt security on after the fact. Shared layers, broad access, and policy promises instead of structural guarantees.
PLATFORM
Secure AI Agent Platform
MightyBot ships enterprise controls by architecture: SOC 2 Type II, tenant isolation,
sensitive-field encryption, managed VPC.
Why MightyBot
MightyBot is a secure AI agent platform for regulated workflows: SOC 2 Type II certified, with tenant isolation, sensitive-field encryption, scoped agent access, and evidence-linked audit trails. Deployment runs in a secure managed VPC with enterprise authentication, and customer data is never used to train models.
Security Is the Architecture.
How MightyBot is built
Multi-tenant isolation, encryption, and scoped access controls are part of the core architecture. They are not optional add-ons.
What enterprises should ask
Does the architecture enforce tenant isolation, encryption, scoped access, and auditability by design, or does it only document what should happen?
MightyBot's answer
In MightyBot, customer data, policies, and execution contexts remain isolated by design. Your data and policies are yours alone.
Security controls for AI agents in regulated industries
| Control | What it means here |
|---|---|
| SOC 2 Type II | Audited controls cover data storage, processing, access controls, encryption practices, incident response, and change management. SOC 2 reports are available under NDA. |
| Tenant isolation | Customer data, policies, and execution contexts remain isolated by design, with no shared data layer between tenants. |
| Sensitive-field encryption at rest and in transit | TLS 1.2+ protects connections, AES-256 protects data at rest, and designated sensitive fields are encrypted independently. |
| Scoped agent credentials | OAuth2 uses scoped permissions, JWT uses scoped claims, and API keys are tenant-scoped, rotatable, and usage logged. |
| Managed VPC deployment | Secure managed VPC deployment uses private network segments and segmented processing tiers for internal services. |
| No model training on customer data | Customer data is processed only for the contracted service scope and is not used to train shared models. |
| Evidence-linked audit trails | Agent workflows preserve evidence-linked audit trails. See AI agent compliance for the audit-trail hand-off. Every API call has a full audit trail. |
SOC 2 Type II Certified
Type I confirms controls exist at a point in time. Type II confirms those controls have been operating effectively over an extended audit period. MightyBot holds Type II certification.
The audit covers the entire platform: data storage, processing pipelines, access controls, encryption practices, incident response, change management. Not a subset. The whole stack.
Audit reports available under NDA.
Multi-Tenant Isolation
Each customer's data resides in logically separated storage with independent access controls. Agent execution occurs within isolated compute contexts. No shared data layer between tenants.
One customer's documents, policies, and decision records are architecturally inaccessible to another customer's agents or users. This isolation extends to the search layer: per-workflow repositories scope results to the authenticated tenant's data.
Your data and policies are yours alone. Architecturally guaranteed.
Sensitive Field Encryption
In Transit TLS 1.2+ for all connections.
At Rest AES-256 encryption.
Field Level Designated sensitive fields (SSN, account numbers, tax IDs) encrypted independently within otherwise accessible records. Explicit permissions required for each sensitive field. Encryption granularity matches access control granularity.
Secure Managed VPC Deployment
External Edge
External traffic passes through load balancers and web application firewalls before reaching any internal service. Public internet exposure limited to this layer only.
Private Network Segments
Internal services communicate through private network segments unreachable from the public internet.
Segmented Processing Tiers
Network segmentation between processing tiers. Document ingestion, data extraction, agent execution, and data storage each operate in separate segments. A breach in one does not propagate to others.
Authentication and Access Control
OAuth2
Scoped permissions, encrypted tokens. For connecting MightyBot to your enterprise systems with full auditability.
JWT
Signed tokens with short expiration and scoped claims. Internal service communication authenticated at every hop.
API Keys
Scoped to tenants, rotatable, usage logged. Full audit trail on every API call. Rotation without service interruption.
Role-based access control granular to the workflow, document, and field level. See non-human identity context for agent credentials.
Data Ownership and Retention
Your data is yours. Customer data is not used for training models, not shared with other customers, and not used outside the contracted service scope. Your policies, rules, and workflows remain your property. It is in our terms.
Retention periods are configurable per data type. When periods expire, data is archived to customer-controlled storage or securely deleted. Your choice. These controls support regulated workflows in financial services.
See production-grade security for your workflows.
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.SystemsEnterprise IntegrationsConnect systems of record to systems of action without rip-and-replace.AuditCompliance InfrastructureWhy-trails, review gates, evidence records, and examiner-ready exports.Measured evidenceAgent Evaluation Cost StudyMeasured token costs of single-pass, agentic, and voting configurations on the same workload.
FAQ
Frequently Asked Questions
How do you secure AI agents in regulated industries?
Constrain what the agent can touch (scoped credentials, tenant isolation), constrain what it can decide (policy-gated actions with human review thresholds), and record everything (evidence-linked audit trails). Security reviews then examine controls and records rather than promises.
What does SOC 2 Type II mean for an AI agent platform?
A SOC 2 Type II report means an independent auditor tested the platform's security controls over a period of time, not just their design on paper. For an AI agent platform it covers the controls around data handling, access, and change management that agent workflows depend on.
Is MightyBot a secure AI agent platform?
Yes. MightyBot is SOC 2 Type II certified, uses tenant isolation, encrypts data at rest and in transit, supports secure managed VPC deployment, and keeps customer data out of shared model training.
How does multi-tenant isolation work?
Customer data resides in logically separated storage with independent access controls and isolated compute. There is no shared data layer between tenants. Isolation is enforced at the infrastructure level.
Does MightyBot encrypt data at rest and in transit?
Yes. TLS 1.2+ in transit, AES-256 at rest, and field-level encryption for designated sensitive values with granular access controls.
Can we deploy MightyBot in our own cloud environment?
The standard model is a secure managed VPC deployment. If you have specific deployment constraints, MightyBot can review those requirements with your team.
Does MightyBot use customer data to train models?
No. Customer data is processed only for the contracted service scope. It is not used to train shared models and is not shared with other customers.
Is MightyBot tied to a single AI model?
No. The platform is model-neutral: execution style is chosen per task, whether that is parallel execution, step-by-step reasoning, or a planned sequence. Customer data is never used to train shared models regardless of which model runs a task.
How are API credentials managed?
Credentials are encrypted at rest, access is restricted to the components that need them, usage is logged, and rotation can occur without service interruption.
Last reviewed: August 6, 2026