Secure the Data. Liberate the AI.
Built by the team that built AWS security and compliance services from the ground up — because we watched cloud-era tools fail at the agentic layer.
Start with the AI visibility your security and compliance teams need to approve agent rollouts on Day 1. Grow into the enforcement and intelligence your Security team will need as agents scale.
Zero code changes · Sub-50ms latency · AWS · Azure · Snowflake · Kubernetes
Proud member companyWhy traditional IT security is failing
Legacy tools check who can access data.
SmartVerify sees what AI actually does with it.
Legacy tools only see infrastructure and resource-level interactions, and try to infer risk from there. SmartVerify sits inside the conversation your AI is having with your data and knows exactly what happened at the data level.
No inference. Direct observation. A precise, forward-looking understanding of AI risk.
Today: Access Control
Checking ID and boarding pass at the gate
Who are you? What resources (terminal, gate) do you have access to? Once an agent is past the perimeter, no one is watching what it actually does with your data.
SmartVerify: Action Control
X-raying every request
Every query and every response is inspected on the data path, checked against your policy, and logged for every interaction.
The gap every existing tool misses
TSA checks your boarding pass at the gate. That answers one question: were you authorized to enter? But once you're airside, there is no record of which shops you entered, what you touched, or what you put in your bag. If something goes missing, "the passenger had a valid boarding pass" is not a defense.
That is the AI compliance problem. IAM tells you who was authorized. SmartVerify tells you what they actually did — per query, per agent, in real time, at the data layer.
IAM / Cloud Security
Who got in
Controls identity and authorization at the perimeter. Goes silent the moment an authorized agent begins querying data.
SmartVerify
What they did inside
Intercepts every query at the data layer. Records what was asked, what was returned, and whether policy was enforced. Per query. Tamper-evident. Framework-mapped.
Data Governance
Where data lives
Catalogs data at rest. Cannot observe what AI agents do with it in real time, especially across vector stores and RAG pipelines.
SmartVerify is not a replacement for IAM or data governance. It fills the gap between them.
Your AI security journey
Start with what the law requires today. Grow into what your AI program will need next.
Today
Meet the law.
AI regulation has arrived. TRAIGA, the Colorado AI Act, California DROP, and the EU AI Act all create liability around what your AI systems did with data, and you cannot defend what you cannot see. Start with a complete, immutable record of every AI interaction with your data.
- An audit trail your Legal team can show a regulator
- Approve agents on Day 1 instead of blocking them
- Visibility into AI you may not even know is running
Tomorrow
Manage AI broadly.
Once you can see what your AI is doing, you will need to do something about it. As more teams ship agents, manual review cannot scale. Move from visibility to real-time control on the data path itself.
- Block unauthorized data access before it leaves the wire
- Redact sensitive fields automatically, without code changes
- Honor deletion requests across vector stores, RAG, and caches
The day after
See what humans and dashboards cannot.
AI expands the scope of security. It is no longer about responding to a single breach event after it happens. It is about catching the slow, distributed exfiltration patterns that no human eye and no dashboard will ever spot — across thousands of agent queries that each look innocent on their own. That is what SmartVerify Intelligence is built to deliver.
- Score the intent of every query, not just the credentials
- Detect exfiltration patterns that span hours, agents, and queries
- Catch agents whose behavior quietly drifts from their baseline
Where we fit
Most security and compliance tools answer the wrong question. They tell you who was authorized, where data lives, or how your environment is configured. None of them answer the question regulators are now asking: what did your AI agent actually do with the data?
| Question | Cloud Security / IAM | Data Governance | AI Posture | SmartVerify |
|---|---|---|---|---|
| What data did our AI agent access on Tuesday? | ✗ | ✗ | ✗ | ✓ |
| Can you prove you monitored for discriminatory access patterns? | ✗ | ✗ | ✗ | ✓ |
| Did any opted-out user's data appear in an AI response? | ✗ | Partial | ✗ | ✓ |
| What's the NIST AI RMF evidence trail for our safe harbor? | ✗ | ✗ | ✗ | ✓ |
| Can you block a bulk data extraction attempt in real time? | Partial | ✗ | Partial | ✓ |
| Is there an immutable per-query log for our auditors? | ✗ | ✗ | ✗ | ✓ |
| Question | AI Posture | SmartVerify |
|---|---|---|
| What data did our AI agent access on Tuesday? | ✗ | ✓ |
| Can you prove you monitored for discriminatory access patterns? | ✗ | ✓ |
| Did any opted-out user's data appear in an AI response? | ✗ | ✓ |
| What's the NIST AI RMF evidence trail for our safe harbor? | ✗ | ✓ |
| Can you block a bulk data extraction attempt in real time? | Partial | ✓ |
| Is there an immutable per-query log for our auditors? | ✗ | ✓ |
See full comparison on desktop
Existing tools are not inadequate — they do what they were designed to do. They were designed for a world before autonomous AI agents. SmartVerify was purpose-built for what comes after.
Model Context Protocol
Zero-Trust Security for MCP Servers
Claude and other MCP clients reach your data through tool calls your existing controls cannot see. SmartVerify inspects every one of them, inline.
Tool-call inspection
See which MCP tool was invoked, with which arguments, and what came back — at the data path.
Intent scoring for agentic payloads
Every agentic request is scored in real time against the agent's behavioral baseline.
Zero-code proxy deployment
No changes to MCP servers or clients. The inline proxy sits on the network path, inside your VPC.