Solutions
IntentFrame helps teams deploy AI agents into real workflows: support, refunds, operations, platform products, regulated processes, internal tools, and infrastructure. The common requirement is simple: the agent can propose, but it cannot approve itself.
Pain: humans still approve agent actions, so the ROI never lands.
For e-commerce, marketplaces, travel, and SaaS teams automating support, refunds, replacements, and account actions.
Pain: one downstream incident becomes your headline.
For AI-agent startups, SaaS products, and platforms shipping agents to their own customers.
Pain: prompts and logs are not enough. Reviewers need enforced boundaries and evidence.
For banks, insurers, healthcare, and compliance-heavy teams blocked by security review.
For Operators
Customer-facing agents can save huge amounts of time, but only if they can actually take action. IntentFrame lets them issue approved refunds, update orders, and resolve workflows while blocking actions that cross your business rules.
Remi reads customer messages and proposes refunds. The business policy is clear: refunds under $100 are allowed only for genuine manufacturing defects.
“The motor died after two weeks.”
Manufacturing defect
✓ ALLOW“I dropped it down the stairs.”
Customer fault
✕ BLOCK“I do not like the color.”
Buyer's remorse
✕ BLOCKThe dollar amount is the same. The action is the same. The meaning is different. That difference is why support automation still gets stuck in human review.
Agents can draft a response, but a human still approves the money.
Agents can identify an issue, but a human still checks policy.
Agents can summarize intent, but not safely mutate records.
Humans become the approval API for every uncertain case.
IntentFrame checks proposed actions against limits and plain-English policy before execution. Low-risk actions move at machine speed. Unsafe actions stop.
For Agent Builders
If your product gives customers an agent that can act, your customer inherits the risk. IntentFrame gives your product an enforcement boundary, audit trail, and deployment story that enterprise buyers can understand.
Agent products are powerful because they touch customer systems. That also means a bad tool call, unsafe refund, unauthorized promise, or destructive command becomes a vendor-risk event.
IntentFrame can sit between your agent and its tool calls. Use the SDK for Python stacks, call the HTTPS endpoint for non-Python stacks, or integrate through a tool gateway.
Shipping an agent product? Do not ask your customers to trust your agent. Give them proof that the agent cannot cross the lines they set.
For Regulated Teams
Regulated teams cannot rely on system prompts as access controls. IntentFrame creates a runtime boundary: the agent proposes, policy is checked outside the agent, credentials stay with the executor, and each decision can be recorded.
Per-action intent records and runtime evidence.
Data-layer enforcement, not just instructions in prompts.
Control evidence around authorization, logging, policy, and review.
Runtime control, decision evidence, and separation between recommendation and execution.
IntentFrame supports compliance evidence and control mapping. It does not make your organization compliant by itself and should be evaluated with your legal, security, and compliance teams.