SolonGate

Zero-trust security gateway for AI agents

Developer ToolsArtificial IntelligenceSecurity

▲ 70 votes6 commentsLaunched Jun 17, 2026

Daily #24Weekly #100

AI agents don't just chat anymore; they execute. SolonGate is the zero-trust security layer that controls exactly what your autonomous AI agents can do. We sit directly between LLMs and your internal systems, APIs, or databases. Every action your AI attempts is filtered through our deterministic Policy Engine and an isolated AI Judge. We block risky, unauthorized, or destructive actions before execution. Complete action governance.

AI Analysis

📝 Summary

SolonGate is a zero-trust security gateway for autonomous AI agents. It intercepts actions between LLMs and internal systems, APIs, or databases, filtering every request through a deterministic Policy Engine and an isolated AI Judge. Risky, unauthorized, or destructive actions are blocked before execution, providing complete action governance. It solves the critical pain point of unsecured AI agents that can cause data breaches, unauthorized access, or system damage when moving beyond chat to real-world execution. The value proposition is secure, controlled AI autonomy for enterprises, enabling safe integration of powerful agents without compromising internal infrastructure.

📈 Market Timing

2025-2026 will see explosive growth in autonomous AI agents across enterprises, with maturing LLM capabilities and rising integration into workflows. User demands for safe, governed AI execution are surging amid high-profile AI incidents and regulations like the EU AI Act emphasizing risk management. Economic focus on AI productivity makes security layers essential. This is an Excellent Timing for SolonGate as zero-trust solutions for agents address an immediate and growing gap before widespread adoption creates larger vulnerabilities.

✅ Feasibility

Technical implementation is challenging but achievable using existing policy engines (e.g. OPA) combined with LLMs for judgment, though ensuring low-latency, accurate AI judging and isolation requires expertise. Development and operation costs are medium-high for a security product needing constant updates. Compliance risks around data privacy and AI regulations are significant but standard for the space. Scalability via cloud deployment is strong. Overall rating: High, assuming an experienced team in AI security.

🎯 Target Market

Main target segments: AI/ML engineers, developers building autonomous agents, CTOs and security teams in mid-to-large tech companies and enterprises (finance, healthcare, enterprise software). Primarily US and Europe-based. TAM for AI safety and security tools projected around $10B+ by 2026, with SAM for agent-specific gateways ~$1B. Core pain points include preventing agent-induced breaches and ensuring compliance. High willingness to pay, as enterprises allocate significant budgets for AI governance and zero-trust solutions (likely $5K-$50K+/year).

⚔️ Competition

Medium. Direct competitors: 1. Lakera.ai (lakera.ai) - LLM security platform against injections and attacks. 2. Guardrails AI (guardrailsai.com) - Open-source framework for LLM output validation. 3. NeMo Guardrails (nvidia.com) - NVIDIA's toolkit for conversational guardrails. 4. Aporia (aporia.com) - AI security and observability platform. Advantages: Specialized zero-trust focus on AI agents with dual deterministic Policy Engine + AI Judge for proactive blocking. Disadvantages: Newer entrant with less brand recognition; may have higher integration complexity compared to established guardrail libraries; pricing transparency unknown but likely enterprise-oriented.

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