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Impart Security secures $12 million in Series A funding led by Madrona to expand its Application Detection and Response (ADR) Engineering Platform. The platform enables security teams to build, test, and deploy custom threat-blocking rules with confidence in production environments. Leveraging WebAssembly and AI, it reduces deployment times and improves incident response without compromising system stability.
Why Today’s Security Tools Still Fall Short in Production
Security teams often encounter tools that perform well during demonstrations but never reach full deployment in live environments. These tools detect complex threats and visualize real-time responses with speed and precision. Despite their capabilities, when the question arises whether the tool can auto-block threats in production, teams hesitate. The lack of trust results in these systems remaining in perpetual monitoring mode, rarely being allowed to act autonomously.
This situation highlights what Impart Security defines as the “last mile problem” in application security. While detection is frequently effective, execution in real-world, production-level scenarios is where systems often fail or are deliberately constrained. The cost of tuning, maintaining, and adjusting black-box solutions remains high, leading to limited rule implementation and growing inefficiencies.
How Impart Security Flips the Script on Application Protection
Impart Security introduces an Application Detection and Response (ADR) Engineering Platform that diverges from the standard model. Instead of offering another opaque system, the company provides a framework that grants security teams full control over their detection and response strategies.
The platform allows teams to:
- Understand their application’s normal behavior patterns.
- Build and test security rules using a dedicated framework.
- Deploy these rules with precision and predictability.
The platform removes the reliance on generic threat feeds and unverified detections. It equips teams to develop custom logic that aligns with specific application contexts. This engineering-centered approach focuses on giving users the confidence to enable autonomous threat blocking in production without uncertainty.
Inside the $12 Million Series A Backed by Madrona
Impart Security secured a $12 million Series A investment led by Madrona. The funding marks a significant milestone, reinforcing confidence in the platform’s capability to solve longstanding issues in the security space.
During the diligence process, Madrona’s team engaged directly with Chief Information Security Officers (CISOs) to evaluate the operational relevance of Impart’s solution. The result confirmed the demand for a platform that enables secure, automatic enforcement in real-time systems.
Karan Mehandru of Madrona brings go-to-market expertise that will support the company’s sales and platform expansion. This partnership aims to scale operations while keeping focus on safe, controllable AI in production environments.
WebAssembly: The Secret Weapon Behind Performance and Safety
Impart’s team identified WebAssembly (WASM) as a key enabler in achieving safe and efficient rule execution. WASM delivers ahead-of-time compilation, allowing rules to operate at near-native speeds under demanding traffic conditions. Its isolation properties make it valuable beyond performance.
WASM creates secure execution environments—sandboxes—where AI agents can analyze traffic patterns, test rule logic, and refine threat detection strategies. This process occurs without exposing production systems to risk.
Security teams can observe how detection models behave in realistic environments without worrying about disruptions or unintended consequences. Deployment flexibility across multi-cloud and edge environments further strengthens the case for WASM’s integration into Impart’s platform.
Early Results That Prove the Model Works
Impart’s deployments already show tangible improvements in production performance and response times. The platform has successfully executed over 2,400 custom rules across customer environments.
Key outcomes include:
- Reducing average rule deployment time from 18 days to 45 minutes.
- Maintaining 99.97% uptime in production environments.
- Shifting team resources away from managing false positives.
Customers have reported operational changes once they trusted the platform’s blocking capabilities. One organization saw its security team move from spending 60% of its time triaging false alerts to focusing on threat hunting and strategic planning.
During newly disclosed CVEs, Impart’s AI is capable of analyzing vulnerabilities, creating detection logic, and safely deploying it within hours. This shortens the traditional cycle, which often takes days for manual implementation and testing.
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Why CISOs and Security Teams Start Paying Attention
As the platform gains traction, CISOs recognize the shift from static detection to actionable intelligence. Confidence in automatic blocking grows when teams can build and test rules tailored to their infrastructure.
Security professionals note that trust must be earned through reliability and transparency. Impart’s approach allows teams to retain visibility and control over how decisions are made and implemented.
The shift also impacts workflows. By reducing noise from generic alerts, teams regain time for proactive initiatives. The ability to respond to new attack patterns with customized protection strategies changes how organizations manage incident response and risk.
What Makes Madrona the Right Partner for Scale
Madrona’s involvement brings more than funding. During the evaluation phase, the team held detailed conversations with security leaders to understand real-world concerns. This grounded approach validated that Impart is not just building advanced tooling, but solving operational issues that matter at scale.
Madrona shares a vision for enterprise infrastructure where AI enhances reliability without introducing unpredictability. Their experience in helping enterprise software scale aligns with Impart’s needs for growth in sales and technical adoption.
The collaboration is based on a mutual understanding of how to integrate AI into high-stakes environments while maintaining safety, auditability, and operational discipline.
Challenges That Still Need Solving
Building autonomous systems that operate safely in production is not just a technical hurdle. Security teams often equate “autonomous” with “unpredictable.” Impart has learned that education is essential.
Different industries bring different risk profiles. What works for a SaaS provider may not be acceptable for a healthcare or financial institution. This variability requires adaptable strategies and ongoing refinement of platform capabilities.
Impart recognizes the importance of continuing to build trust by focusing on system transparency, customization, and gradual enablement of autonomous features.
Why This Milestone Matters for the Future of Security Operations
The $12 million investment reflects industry demand for application security solutions that move past passive monitoring. By solving the last mile problem, Impart shows that AI can support real-time protection without sacrificing control or reliability.
Deployments to date demonstrate that production environments can adopt customized, AI-assisted blocking that adapts faster than threat actors. Impart’s approach to security enables teams to build defenses with confidence, precision, and verified impact.
The platform represents a shift from abstract detection toward controllable, testable action—making production environments not just monitored, but defended in real-time.
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