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 is a platform of four specialized products: SecureMind (DLP + privacy), Breach-Intel (agent security + breach intelligence), Sentinel (monitoring + knowledge graph), and SecureRapidClaw (rapid response + containment). Together they cover the full AI agent security lifecycle — built to be model-agnostic, local-first, and operational in 30 seconds.

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Our Mission

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.

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Our Vision

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.

Principles

What drives us

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Transparency

Every security decision is logged, explained, and auditable. No black boxes.

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Integrity

SHA-256 hash chains, immutable writes, tamper detection on every read.

Simplicity

Install the extension, security is active. Zero config, zero code changes.

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Open Core

The full security engine is open source. Enterprise features layer on top.

Origin Story

Why we built this

One problem. Seven layers. Zero compromise.

We watched AI coding assistants get deployed across enterprise teams with zero security controls. Copilot could read .env files. Claude Code could execute cat ~/.ssh/id_rsa. LangChain agents could exfiltrate customer data through API responses. Every compliance framework was being violated silently.

The existing solutions were vendor-specific (GitHub's content exclusions only work with Copilot), reactive (secret scanning catches committed secrets, not prevented reads), or required massive infrastructure changes.

So we built the SecureMind platform So we built SecureMind — a model-agnostic security platformmdash; four specialized products (SecureMind, Breach-Intel, Sentinel, SecureRapidClaw) forming a model-agnostic security suite that intercepts file reads, commands, prompts, API calls, and responses across ALL AI coding tools. Seven layers of defense, working with any LLM provider, running entirely on the developer's machine.

The result: install once, everything is protected. Swap from Copilot to Claude Code to Cursor — same DLP policies, same audit logs, same compliance rules.

Team

The people behind the SecureMind platform

PM

Partha Mehta

Co-Founder

KD

Kaushik Dharamshi

Co-Founder

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Join Us

Open Roles

Timeline

Building in public

Q1 2026 — January

SecurityAgent for OpenClaw

Built the initial DLP plugin for OpenClaw — file read gate, exec command guard, and prompt intent analysis.

Q1 2026 — February

Model-agnostic gateway

Launched the FastAPI security proxy supporting OpenAI, Anthropic, Gemini, Azure, and GitHub Models with PII redaction and injection detection.

Q1 2026 — March

VS Code extension + Chrome extension

Shipped the Copilot guardrail extension with multi-assistant support (Copilot, Cursor, Windsurf, Cody) and a Chrome DLP guard for browser-based AI tools.

Q1 2026 — March

securityagent-core extraction

Extracted the DLP engine into a reusable package. SecureMind and SecurityAgent both consume the same core.

Q2 2026 — April

Privacy controls + v4.0.0

Added system prompt masking, media filtering, AES-256-GCM session encryption, and modifying output pipeline. False-positive elimination across the full DLP stack. 248+ automated tests.

Q2 2026 — April

Effect-layer defenses

Shipped taint tracking, egress allowlist, lethal trifecta detector, tool call argument scanning, and code scanner for embedded secrets.

Secure your AI agents today.

Whether you're using Copilot, Claude Code, Cursor, or LangChain — we'd love to hear from you.

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