AI Governance for B2B SaaS.
Growth-stage and enterprise B2B SaaS companies are shipping AI features into customers in healthcare, financial services, insurance, and government. Those customers send security questionnaires, DPAs, and audit requests that the LLM provider terms of service alone cannot answer. The gateway between the SaaS application and the LLM provider is where SOC 2, ISO 27001, GDPR Article 28, CCPA, and customer DPA obligations need to be applied.
DeepInspect runs inline in front of the AI provider. Customer-tenant data, sensitive identifiers, and customer-supplied content are detected and transformed before the payload leaves the SaaS company's environment. Every decision is written to a tamper-evident forensic record with the policy version, the actor identity, the tenant context, and the original and transformed payloads preserved. The same configuration applies to the customer-facing AI feature, internal copilots, and autonomous agents that act on tenant data.
The risk surface for a SaaS AI feature
Customer-tenant data crossing the LLM boundary
The AI feature reads tenant data (customer records, support history, CRM fields, uploaded documents) and forwards it to the LLM provider. The DPA the SaaS company signed with the tenant covers what happens to that data inside the SaaS environment. Once the payload reaches the LLM provider, only the LLM provider terms apply, which is rarely what the tenant DPA describes.
Customer security questionnaires that already ask about AI
Procurement and security teams at regulated customers now include 20 to 80 AI-specific questions in the vendor review. Answers depend on artifacts: data flow diagrams, sub-processor lists, redaction documentation, audit logs, and incident response runbooks. The deal slows or stalls when those artifacts are missing.
Prompt injection in customer-supplied content
Customer-uploaded documents, support tickets, web content, and CRM records are the most common prompt injection vector for B2B SaaS AI features. An untrusted input that overrides the system prompt can exfiltrate tenant data, escalate agent permissions, or move into adjacent tenants. The control needs to live at the request layer, not at the LLM provider.
Cost and abuse on a per-tenant basis
Token costs are a real line on the P&L. A single tenant on an unbounded feature can move the gross margin by single-digit points. Per-tenant attribution, rate limits, and a kill switch on the AI path are operational requirements, not nice-to-haves.
How DeepInspect applies controls
Sensitive data detection and transformation
Deterministic detectors match PII, PHI, PCI, and customer-specific data classes the tenant configuration declares. Each match is redacted, tokenized, or blocked according to the configured action for the tenant and role in effect. Tokenization keeps a reversible mapping inside the SaaS environment so the model response can be re-hydrated for the end user.
Per-tenant identity-aware policy
Tenant identity is carried on every AI request. The gateway evaluates the per-tenant action map at request time and applies the matching transformation. A healthcare tenant can have PHI detection set to block while a marketing-tech tenant has redaction only. The tenant policy version is preserved on every record.
Audit-ready forensic record per tenant
Every interaction writes a signed record containing the tenant identity, the actor identity, the policy version, the rule evaluation path, the original payload, the transformed payload, and the upstream response. The record set is exportable per tenant for customer audits, GDPR Article 28(3)(h) audit rights, and SOC 2 Type II evidence.
Prompt injection on customer-supplied content
Adversarial inputs in uploaded documents, support tickets, and CRM records are scored against the configured detectors and blocked or routed to escalation according to policy. The score, the input, the action, and the originating tenant are preserved in the forensic record.
Token cost attribution and per-tenant rate limits
Token-level cost attribution writes a per-tenant ledger entry on every AI interaction. Per-tenant rate limits and model routing across pools keep cost predictable and let the finance team price the AI feature on real data. The organization-wide kill switch shuts off the AI path during an active incident.
Tool and agent allowlists for customer-facing agents
Customer-facing agents reach the SaaS application's own APIs and any third-party tools the agent invokes. The gateway enforces allowlists and blocklists on the tools an agent invokes and the data sources it reads. An agent that attempts to call a system outside its allowlist is stopped at the gateway with a record of the attempt.
Framework mapping
SOC 2 Trust Services Criteria
The CC6 logical access, CC7 system operations, and CC8 change management criteria all expect contemporaneous, attributable evidence on production data paths. The gateway record covers the AI path with the same evidence standard the auditor already accepts for the rest of the platform.
ISO 27001 and ISO 42001
Annex A.8 asset management, A.5.7 threat intelligence, and the operational controls A.8.16 monitoring and A.8.34 protection during audit testing map directly to the gateway record. ISO 42001 AI management system clauses on operational planning, performance evaluation, and continual improvement build on the same record.
GDPR Article 28
The LLM provider is a sub-processor. The gateway enforces the contractual boundary the DPA defines and produces the audit evidence Article 28(3)(h) calls for. The forensic record covers Article 30 records of processing activities for the AI path.
CCPA and CPRA
Consumer data handled by the AI feature is in scope for CCPA. The gateway preserves the audit record needed to respond to access, deletion, and opt-out requests on the AI path.
EU AI Act
SaaS companies shipping AI features into high-risk use cases inherit obligations under the AI Act. Policy versioning produces the change-control trail relevant to Article 17. The forensic record covers Article 12 record-keeping. Inline enforcement with fail-closed default behavior addresses Article 9 risk management.
Customer DPAs and outside auditor requests
A single record set, exportable per tenant, answers the audit and DPA inquiry that comes back during the customer's annual vendor review. The artifact is the same one the SaaS company uses internally for SOC 2 evidence.
The scale of the gap
of organizations reported confirmed or suspected AI agent security incidents in the past year. SaaS companies shipping AI features inherit that risk surface on behalf of every regulated tenant.
of organizations report that their entire AI agent fleet went live with full security and IT approval. The remainder shipped customer-facing AI features outside the standard review pipeline that governs the rest of production.
is the global average cost of a data breach in 2024. The number is consistently higher for multi-tenant SaaS breaches because the notification population spans every regulated customer affected.
of teams treat AI agents as identity-bearing entities. The remainder authenticate agents with shared API keys or hardcoded credentials, which makes per-tenant attribution and revocation impossible.
Deployment
The gateway runs self-hosted in the SaaS company's VPC or on-premises. SaaS and hybrid deployments are available for organizations with different sovereignty requirements. Tenant data, the forensic store, and the transaction object store stay inside the SaaS company's boundary in every configuration.
DeepInspect sits inline between the application service and the AI provider. It works with OpenAI, Azure OpenAI, Anthropic, Bedrock, and internal models without requiring a model migration. Existing IdP, SIEM, billing, and feature-flag integrations stay in place. Production cutover typically lands inside two weeks for a defined feature scope.
Policy on every AI interaction, per tenant, enforced before data leaves the boundary.