Agent firewall
Authorize or block every tool call — email sends, database writes, payment actions — before execution.
SoterAI inspects every prompt, response, retrieval, and agent tool-call in real time — blocking prompt injection, redacting sensitive data, and turning every risky interaction into evidence your team can trust.
The problem
Untrusted prompts, copied secrets, personal data, and unsafe model responses need controls outside the model itself. SoterAI adds an observable security gateway to the flow.
2-way
Input, output, and agent coverage
Risk reduction around users, models, retrieval, and tools.
Operating model
Evaluate every user message before model execution.
Block, redact, rewrite, or route high-risk traffic for review.
Check model responses before users or downstream tools see them.
Use dashboards, logs, webhooks, and reports to improve controls.
Two platforms, one security layer
Whether your AI agents act on company systems or your employees use AI tools with sensitive data — SoterAI protects both sides.
For companies using AI agents
Your AI agents use email, CRM, database, and payments. SoterAI gives you action approval, audit logs, rollback, and compliance — a high-trust control layer between agents and your business systems.
For 50-500 employee companies
Employees paste company data into ChatGPT, Claude, and Cursor daily. SoterAI enforces provider policies, department rules, data classification, and keeps a complete audit trail for legal accountability.
Defense in depth
SoterAI sits between users, models, retrieval systems, and agents, turning risky behavior into explainable decisions.
Authorize or block every tool call — email sends, database writes, payment actions — before execution.
Hold risky actions for human review. Stage compensating actions for safe rollback with full audit trail.
Cryptographically signed agent passports with capability-based authorization and delegation chains.
Different AI rules for engineering, marketing, finance, and HR. Block ChatGPT for finance, allow Claude for engineering.
Detect when employees paste company data, customer records, or credentials into AI tools and block or alert.
Complete audit trail with compliance reports. Know who used which AI tool, when, and with what data.
Detect instruction overrides, jailbreak personas, prompt extraction, and tool-abuse attempts before they reach the model.
Redact PII, India-specific identifiers, credentials, tokens, and database URLs without storing raw secret values.
Inspect retrieved context, document trust, and memory records so private data does not quietly move into unsafe outputs.
Check model responses for leaked instructions, unsafe claims, sensitive data, suspicious links, and policy violations.
Convert findings into risk scores and actions: allow, redact, rewrite, human review, or block.
Track decisions, redactions, blocked requests, usage, webhooks, and monthly security summaries for operations teams.
See it in action
An interactive walkthrough showing prompt injection blocking, India PII redaction, secret detection, jailbreak prevention, and our F1=1.0000 benchmark in action.
User message
Risk score
BLOCKED
Action
BLOCK
Request blocked before reaching LLM. No data exposed.
Prompt Injection Blocked
Instruction override attempt detected and stopped in real-time
Adversarial Benchmark
97/97 adversarial cases detected with 0/25 false positives in a small, self-authored dataset. This Garak-style evaluation is useful regression evidence, not an independent audit or production guarantee.
100%
Detection Rate
97/97 adversarial prompts
0%
False Positives
25/25 safe inputs allowed
891ms
Recorded HTTP p50
Internal benchmark run
8
Attack Categories
All detected at 100%
OWASP alignment
Controls map to relevant OWASP LLM Top 10 risk areas. Alignment supports risk reduction and is not a certification or claim of complete coverage.
Detect instruction overrides, jailbreak combinations, and prompt extraction attempts.
Redact PII, Indian identifiers, credentials, tokens, and database URLs.
Inspect model output for leaked instructions, unsafe claims, and suspicious links.
Apply text-size, per-minute, and monthly usage controls.
Built for India
Detect and redact Aadhaar-like patterns, PAN, GSTIN, UPI, IFSC, Indian mobile numbers, and contextual student, patient, and bank identifiers.
Interactive playground
Use safe defensive examples to inspect findings, redaction, action, and risk score.
Plans
Pricing is a launch preview while billing is finalized.
Free
INR 0/mo
Validate a small AI workflow
Input and output guard
Risk logs
Redaction engine
Starter
INR 999/mo
Protect production chatbot traffic
Input and output guard
Risk logs
Redaction engine
Pro
INR 2,999/mo
Team controls and deeper reporting
Input and output guard
Risk logs
Redaction engine
Agency
INR 9,999/mo
Multi-client security operations
Input and output guard
Risk logs
Redaction engine
Questions
SoterAI is an AI security command layer that protects chatbots, RAG apps, and autonomous agents from prompt injection, jailbreaks, data leakage, unsafe outputs, and agent abuse. It sits between users, models, and tools to inspect every AI interaction in real time.
No. SoterAI is a defense-in-depth risk reduction layer. It should be combined with secure application design, identity controls, monitoring, and human review.
SoterAI inspects AI inputs and outputs for prompt injection, jailbreaks, sensitive data, unsafe responses, and risky agent behavior across chatbots, RAG pipelines, and autonomous agents.
SoterAI uses a multi-layer detection engine that analyzes user inputs for instruction overrides, jailbreak personas (like DAN), prompt extraction attempts, encoding obfuscation, multilingual attacks, and indirect injection through retrieved documents.
Yes. SoterAI offers a Free plan at INR 0/month to validate a small AI workflow. Paid plans start at INR 999/month for production chatbot traffic with team controls, deeper reporting, and priority support.
Yes. The production stack runs with Docker, Postgres, Redis, and optional vector storage, so teams can keep full control of deployment and data boundaries on their own infrastructure.
No. Secret-bearing and sensitive payloads are persisted only in redacted or hashed form where practical. SoterAI is designed to minimize data retention of sensitive content.
Yes. SoterAI is built with India-specific PII detection including Aadhaar-like patterns, PAN, GSTIN, UPI ID, IFSC codes, Indian mobile numbers, and contextual student, patient, and bank identifiers.
SoterAI performs input and output guard checks in under 50 milliseconds, making it suitable for real-time chatbot and agent interactions without noticeable latency.
Create a project, keep your API key on the server, call the input guard before your LLM, and call the output guard before returning the response to the user. SDKs are available for JavaScript, Python, Next.js, Express, and more.
SoterAI provides native SDKs for JavaScript/TypeScript and Python, plus a REST API that works with any language including Java, Go, PHP, C#, Ruby, Rust, and more.
Yes. SoterAI integrates with LangChain chains, LlamaIndex query engines, and custom RAG pipelines. It inspects retrieved context, applies document trust scoring, and prevents sensitive data from leaking into model responses.
Start with the playground, then protect users, models, retrieval, and tools with project-scoped API keys.
Read integration docs