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Clear out junk files and repair common Windows errorsFree Scan →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Qevlar AI announced an additional $10 million in funding on April 8, 2025, bringing investor commitments at the time to $14 million. The Paris-based cybersecurity company builds software that investigates security alerts across existing SIEM and EDR systems, then delivers a verdict, report, and suggested remediation. Its 2025 performance figures are company-reported, not independently audited; Qevlar later announced another $30 million round in March 2026.
Qevlar AI raises $10 million — what does it build?
The $10 million was an additional financing tranche announced on April 8, 2025. Qevlar said it would use the capital to support growth and international expansion, hire across teams, and fund product research and development. SecurityWeek also reported the round and the company’s founding in 2023. Qevlar’s announcement and SecurityWeek’s report describe the funding event.
The amount is not Qevlar’s current cumulative funding history. On March 10, 2026, the company announced a separate $30 million round jointly led by Partech and Forgepoint Capital International, with EQT Ventures participating. Qevlar said that financing would help it expand beyond individual alert investigations toward organization-level security insights. The later-round announcement provides that updated context.
What is Qevlar AI’s autonomous investigation platform?
Qevlar sells an investigation API and AI security operations center (SOC) platform. It connects to an organization’s existing security tools, including security information and event management (SIEM) and endpoint detection and response (EDR) systems. It gathers and enriches internal and external data, correlates activity, investigates an alert, and returns a malicious, benign, or inconclusive verdict. The workflow can also produce an investigation report and suggest remediation. The company describes the platform as autonomous because investigations can start without an analyst initiating them and do not require a prewritten playbook to dictate each step. See Qevlar’s autonomous SOC page.
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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errors#1 Best Overall
- ✅Powered by 26 Tera-Operations Per Second (TOPS) Hailo-8 AI Processor. 2.5W typical power consumption
- ✅Scalable, enabling simultaneous processing of multi-streams & multi-models
- ✅Enabling real-time, low latency and high-efficiency AI inferencing on the edge devices
- ✅Supports TensorFlow, TensorFlow Lite, ONNX, Keras, Pytorch frameworks
- ✅Supports Linux and Windows. Supports the temperature range of -40°C to 85°C
That makes the product different in intent from a tool that only summarizes an alert or assists an analyst after a manual handoff: Qevlar describes a system that carries out the investigation itself. The practical value depends on how well it connects to an organization’s tools, how clearly it supports its conclusions, and what review controls a security team can apply. The available figures do not establish a like-for-like independent comparison with competing SOC automation products.
How does an autonomous SOC investigate alerts?
- Connect to security data: The platform works with existing SIEM and EDR systems rather than requiring an organization to replace them.
- Gather and correlate evidence: It pulls relevant internal and external data, enriches it, and connects activity associated with the alert.
- Reach a verdict: It classifies the case as malicious, benign, or inconclusive. Qevlar’s customer Almond described the desired outcome as a verdict accompanied by a confidence level that could inform subsequent processing.
- Document and recommend action: It generates a report and suggests remediation, giving analysts an account of the investigation and a proposed next step.
In Qevlar’s model, these steps can run without an analyst starting each case or a playbook predefining the investigation path. That is the vendor’s description of its operating model; the supplied public figures do not independently quantify how often analyst review is still needed for particular alert types.
Rank #2
- High-Performance Dual-Core with Ample Memory--- Equipped with a 360MHz dual-core RISC-V processor, 32MB of onboard PSRAM, and 32MB of Flash memory, providing powerful processing capabilities and ample runtime for complex multimedia applications and edge computing.
- Powerful Multimedia Processing Center--- Integrated with a dedicated image processor (ISP), H.264 video encoder, and JPEG codec, perfectly supporting camera input and video processing, making it an ideal choice for developing smart displays, video surveillance, and other projects.
- Hardware-Level Security Protection--- Built-in digital signature, encryption accelerator, and key management unit, providing a one-stop hardware-level security solution from secure boot and data encryption to access control management, ensuring the security of your products and data.
- Full Connectivity Coverage: Wi-Fi 6, Bluetooth, PoE Power Supply--- Onboard with an ESP32-C6 chip, supporting the latest Wi-Fi 6 and Bluetooth 5.0; it also integrates an Ethernet port with PoE functionality, providing high-speed, flexible, and stable network connectivity, and can be powered directly via Ethernet cable, simplifying deployment.
- Rich interfaces and strong expandability--- It provides a MIPI camera/display interface, high-speed USB, SD card slot, microphone/speaker interface and a large number of programmable GPIOs, which greatly facilitates the expansion of external devices and meets the needs of various human-computer interaction and Internet of Things applications. Supports AI Speech Interaction: Allows access to online large model platforms such as ChatGPT, DeepSeek, Doubao, etc.
What performance figures has Qevlar reported?
Qevlar’s April 2025 announcement reported the following results. Forgepoint Capital International reproduced those figures in its own release. They should be read as claims by the company and its investor, rather than independently audited results or a third-party benchmark.
| Reported measure | Qevlar’s April 2025 figure | Qualification |
|---|---|---|
| Time spent on malicious alerts | Reduced from 40 minutes to 3 minutes | Qevlar-reported result; conditions and independent validation were not stated in the announcement. |
| Level 1 and Level 2 analyst time on investigation tasks | 90% reduction | Qevlar-reported result; conditions and independent validation were not stated in the announcement. |
| Classification accuracy | 99.8% | Qevlar’s reported figure; the announcement compared it with a cited 97% maximum for human experts. No independent audit or benchmark was identified. |
| Benign alerts | 100% closed autonomously | Qevlar-reported figure; the announcement did not state an independent validation method. |
Qevlar’s current product page publishes a separate set of operating claims: an average investigation time of 3 minutes, up to 80% of tickets closed without a human, 24/7 unattended investigations, 100% of alerts worked rather than sampled, and more than 1,500 organizations in production. These are current company statements, not independently audited figures. The company’s product page presents them without establishing a third-party comparison or the conditions behind each measurement.
Rank #3
- Powered by 26 Tera-Operations Per Second (TOPS) Hailo-8 AI Processor.
- 2.5W typical power consumption
- Enabling real-time low latency and high-efficiency AI inferencing on the edge devices
- Supports TensorFlow TensorFlow Lite, ONNX, Keras, Pytorch frameworks
- Supports Linux and Windows.
Who invested in Qevlar AI?
EQT Ventures and Forgepoint Capital International led the April 2025 round. The announcement also named three strategic participants: Olivier Pomel, CEO of Datadog; Florian Douetteau, CEO of Dataiku; and Mehdi Ghissassi, formerly Director of Product at Google DeepMind. Forgepoint said its managing director Damien Henault would join Qevlar’s board. The round brought investor commitments to $14 million at that point, according to Qevlar and Forgepoint.
The named technology executives participated strategically; the announcement does not identify them as the round’s lead investors. In March 2026, Partech and Forgepoint jointly led Qevlar’s later $30 million round, and EQT Ventures participated, according to Qevlar’s announcement.
Quick Recap
Rank #4
- High-Performance AI Processing: The MX3 is designed to handle the most demanding AI computer vision workloads, delivering exceptional performance and efficiency.
- Flexible Integration: The MX3 can be easily integrated into your existing systems via its M.2 M-key form factor and support for Linux operating systems.
- Energy Efficient: The MX3 is designed to provide high performance while minimizing power consumption.
- Comprehensive Software Development Kit (SDK): The MX3 is supported by a comprehensive SDK that simplifies development and deployment.
- Hardware compatability: The MX3 is compatible with the PCI-SIG M.2 M-key 2280 Specification. It can be used with the Raspberry Pi 5 with a M-key 2280 HAT.
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