See what your
agents are doing. Stop what they shouldn’t.

AI moves too fast for off-the-shelf controls and quarterly engagements. New agents, new MCP servers, and new attack patterns appear every week. Forward-deployed security applies the forward-deployed engineer model to AI security: engineers embedded directly with your team, with detection and integration tuned to your actual stack. Slack channel, joint oncall, hands-on policy tuning, and new agents wired into your security posture in days rather than procurement cycles.

We control agent actions: tool/MCP calls, identity usage, and sensitive data access, both before and during execution. Not just what an agent says, but what it does.

No. Prompt analysis is one input. The bulk of our value is runtime behavior control: which tools an agent calls, which identities it assumes, which data it touches. We focus on actions, not text alone.

In your infrastructure layer: Bedrock and Azure OpenAI deployments, Vertex and Gemini, Copilot Studio and Agentforce agents, plus the RAG indexes, vector stores and data stores behind them. Wingback discovers each deployment, maps its identity, tool scope and data lineage, and watches every call it makes, so a model that was stood up outside your process still shows up in the same inventory.

The agents in your own products: inference paths, tool calls, and MCP servers, from the prompt that enters the system to the response that reaches a customer. Wingback traces each hop, checks the scope every tool call runs under, and blocks the call when the chain looks like exfiltration or injection rather than normal product behaviour.

The endpoint layer: Claude Code, Cursor, Copilot, local MCP servers, and personal API keys. Sensors on the laptop report which assistants and MCP servers are installed, which keys they use, and which files and commands they touch, so shadow AI on a developer machine is inventoried alongside everything running in the cloud.

All major agent frameworks (LangChain, CrewAI, AutoGen, OpenAI Agents), plus MCP servers, hosted models (OpenAI, Anthropic, Google, Mistral), IDE assistants (Claude Code, Cursor, Copilot), and custom agents via our SDK.

Yes. We catch injection through multi-signal correlation (pattern detection, exfil intent, scope violations, behavioral drift), not just text matching. Most attacks ride downstream actions; that's what we block.

We trace chain-of-custody across every delegation and tool call, so a multi-step workflow bridging three agents still has a single auditable thread. Privilege escalation in handoffs is a first-class detection.

Both. Monitor-only mode for discovery and tuning; enforce mode to block policy violations in real time. Most teams start with monitor, then promote rules to enforce as confidence builds.

Lightweight SDKs for major frameworks, API gateways for LLM providers, an MCP gateway proxy, and cloud connectors for discovery. The forward-deployed team wires it to your exact stack, including in-house frameworks.

Visibility lands in days, not quarters. Most teams have inventory and monitor-mode running in under a week, with enforcement live on the highest-risk paths in week two or three.

Yes. Native integrations with Splunk, Datadog, Snowflake, Chronicle, and standard SIEM webhooks. Every event ships structured so it slots into your existing detection-and-response pipeline.

We maintain a continuously updated model and MCP intelligence registry covering security scores, capability profiles, known vulnerabilities, and scope risks. The policy engine gates which models and MCP servers your agents can use, and under what conditions.

Customer data stays in your environment. Wingback's data plane deploys in three modes: (1) managed SaaS in our AWS regions (us-east-1, us-west-2, eu-west-1; APAC on request), (2) dedicated single-tenant in your hyperscaler of choice (AWS, GCP, or Azure), or (3) self-hosted in your own VPC via Helm chart. In all modes, sensitive payloads stay inside your network boundary. The Wingback control plane receives only structured metadata, traces, and policy events; raw prompts, completions, and tool outputs are inspected inline and either dropped, redacted, or retained per your policy. Encryption-at-rest uses customer-managed KMS keys for self-hosted and dedicated deployments; managed SaaS uses per-tenant CMKs. Retention is configurable from 7 days to 7 years with tamper-evident audit trails. Wingback is SOC 2 Type II certified, ISO 27001 certification in progress, and ISO 42001-mapped. DPAs and right-to-audit clauses are standard in our enterprise agreements.