Deploy an enterprise reverse proxy security shield between LLM APIs (Claude, Gemini, OpenAI) and internal databases. Block destructive SQL, prompt injections, and container escapes with 0ms physical overhead and tamper-proof compliance logging.
MCP Tool Call Request
0ms AST + Air-Gapped SLM
Protected Enterprise Core
Abstract 'A' Node Vector (AI / AIGis Identity): Crafted with precision circuit lines and vector node arrays, symbolizing artificial intelligence nodes operates across enterprise workloads.
Circuit Breaker & AST Laser Cutout: The horizontal crossbar of the 'A' features a physical disconnect laser gap, symbolizing the instant physical trip when AIGis intercepts high-risk DDL or prompt injections.
Geek Terminal & Dark Cyber Aesthetics: Set against a midnight navy background (#02050e) with electric glacier blue and laser emerald beam accents, conveying security authority.
Deploying AI Agents and MCP tools inside corporate environments exposes infrastructure to unmonitored risk. Here is how AIGis eliminates these critical vulnerabilities.
Autonomous Agents or IDE tools executing DROP TABLE or DELETE commands due to prompt manipulation or execution errors, wiping production data.
Generic data masking replaces IPs and Phone numbers with random fake data or static tags, breaking SQL JOIN and GROUP BY referential integrity in data warehouses.
Agents writing custom Python or Shell scripts attempting OS system calls (os.system, subprocess) or obfuscated Base64 payloads to breach container boundaries.
Attackers hiding indirect prompt injections inside documents or database rows, slowly manipulating the Agent's reasoning loop over multiple conversational turns to bypass single-request filters.
Enterprise legal mandates (EU AI Act, Data Protection Acts) strictly prohibiting sensitive data or audit logs from leaving the private corporate LAN.
Code-level physical hard blocking of destructive DDL statements (DROP/TRUNCATE) executing in 0.1ms, combined with an air-gapped local intelligence engine evaluating semantic intent & prompt injection attempts.
In 2026, 87% of enterprises using autonomous AI Agents report unverified tool execution, indirect prompt injections, or unauthorized database mutation attempts.
Transmitting un-sanitized customer PII, internal IP addresses, or database credentials to public cloud LLM APIs poses severe legal and financial penalties. AIGis automatically scrubs passwords, IPs, and phone numbers in-memory.
High-frequency queries bypass LLM evaluation and hit sub-millisecond decision cache, delivering 100K+ TPS throughput with 0 impact on enterprise API latency.
Secures developers using Cursor, Claude Desktop, or IDE Agents connected to internal MySQL/Postgres databases, preventing accidental DDL deletion (`DROP TABLE`) and source code leakage to cloud LLMs.
Prohibits public SaaS gateways. Deploys 100% on-premises to intercept privilege escalations, mask customer PII, and generate DuckDB-queryable Parquet compliance ledgers.
Automatically redacts patient names, phone numbers, real IPs, and medical records before AI analysis, ensuring strict HIPAA & patient data privacy compliance.
Employs SandboxGuard OS syscall firewall to prevent container escape attempts (`os.system`, `subprocess`) with RSA 2048 hardware machine locking.
Test simulated AI inputs and toggle between AST Lexer AST analysis, Layer 2 structured contracts, and audit logging to inspect AIGis internal mechanics.
// Layer 1 Abstract Syntax Tree (AST) & Lexer output will appear here...
// Layer 2 Pydantic Structured Safety Evaluation Contract will appear here...
Ideal for developers, PoC testing, and individual open-source MCP setups.
Designed for mid-sized tech companies and internal AI Assistant deployments.
Tailored for banks, defense units, healthcare, and large Kubernetes clusters.
AIGis never transmits any data to the public internet. Gateway logic, evaluation engine, and audit ledgers are deployed 100% inside your enterprise private LAN, meeting the strictest security compliance standards.