We believe security shouldn't depend on your model choice. Five products. Complete AI agent security coverage.
AI coding assistants are running on developer machines with full access to .env files, API keys, SSH keys, customer PII, and source code. Every compliance framework — PCI-DSS, SOX, HIPAA — requires strict controls over sensitive data access. AI agents bypass every one of them.
SecureMind was built by three engineers — Partha, Kaushik, and Junaid — who kept asking the same question: why does no one secure these agents? The answer became a platform: five specialized products (SecureMind, Breach-Intel, Sentinel, RapidClaw) covering the full AI agent security lifecycle — model-agnostic, local-first, and operational in 30 seconds.
Give every development team enterprise-grade DLP for their AI coding assistants — without vendor lock-in, cloud dependencies, or changes to existing workflows. Security that works with any LLM, any IDE, any deployment model.
A world where AI agents are as accountable as human developers. Every file access logged, every command audited, every prompt screened — automatically, transparently, and without slowing anyone down.
Every security decision is logged, explained, and auditable. No black boxes.
SHA-256 hash chains, immutable writes, tamper detection on every read.
Install the extension, security is active. Zero config, zero code changes.
Everything runs on your machine. Zero cloud dependencies, zero telemetry. Enterprise features available.
Partha and Junaid met as engineering classmates and graduated together in 2019. Kaushik joined their circle around 2018 through a shared passion for table tennis — what started as a casual friendship evolved into a tight-knit group that regularly met to talk about technical careers, industry trends, and ideas worth building.
When LLMs started going mainstream, the conversations shifted. We kept coming back to one question: who is actually securing these AI coding agents that now have full access to developer machines? We researched the space thoroughly — existing tools were either vendor-specific, reactive, or required heavy infrastructure changes. Nobody had built a model-agnostic, local-first security layer that worked across all AI tools simultaneously.
That gap was the startup. We stopped researching and started building — five specialized products forming one complete AI agent security platform: SecureMind (DLP), Breach-Intel (compliance), Sentinel (monitoring), and RapidClaw (rapid response). Zero cloud dependencies. Works with every LLM. Install once, everything is protected.
Co-Founder
Co-Founder
Co-Founder
Open Roles
Built the initial DLP plugin for OpenClaw — file read gate, exec command guard, and prompt intent analysis.
Launched the FastAPI security proxy supporting OpenAI, Anthropic, Gemini, Azure, and GitHub Models with PII redaction and injection detection.
Shipped the Copilot guardrail extension with multi-assistant support (Copilot, Cursor) and a Chrome DLP guard for browser-based AI tools.
Extracted the DLP engine into a reusable package. SecureMind and SecurityAgent both consume the same core.
Added system prompt masking, media filtering, AES-256-GCM session encryption, and modifying output pipeline. False-positive elimination across the full DLP stack.
Shipped taint tracking, egress allowlist, lethal trifecta detector, tool call argument scanning, code scanner. Intelligent LLM routing (14 models, 4 providers, 5 strategies). Admin console with RBAC and agent enrollment.
55-agent Docker red-team harness (84 events, 100% detection). 6-layer Ingress Guard for external agent defense with cross-session reputation. 25 components, 1,150 automated tests across 32 suites.
Whether you're using Copilot, Claude Code, or Cursor — we'd love to hear from you.