An intelligent gateway that sits between your employees and every LLM — redacting sensitive data in real-time, attributing every token to a budget, and routing requests across models for zero-downtime AI operations.
| User | Department | Model | Status |
|---|---|---|---|
| S. Martinez | Engineering | Claude 4 | Passed |
| R. Chen | Marketing | GPT-4o | Redacted |
| L. Thompson | Legal | Gemini Pro | Blocked |
| K. Johansson | Sales | Claude 4 | Passed |
| A. Okafor | Finance | GPT-4o | Redacted |
Kansoforce AI Security Trust Gateway provides enterprise-grade security for AI agent deployments with SOC 2, ISO 27001, GDPR, and HIPAA compliance. The platform enforces Zero Trust architecture with real-time prompt injection detection, data loss prevention, and complete audit trails for every AI interaction across the organization.
Employees paste sensitive code, customer PII, and internal strategy documents into ChatGPT and other LLMs daily. Without a gateway, this data is effectively gone — potentially training public models and creating compliance violations you won't discover until it's too late.
Without centralized tracking, companies discover their AI spend is out of control only after receiving a massive bill. There's no visibility into which department, project, or user is driving the cost — making budget allocation a guessing game.
For regulated industries — healthcare, finance, legal — using AI without an audit trail is a non-starter. You need to know who asked what, when, and whether sensitive data was exposed. Today, most organizations have zero visibility.
The Gateway sits between every employee and every LLM. When someone pastes a customer contract, the AI identifies PII in real-time, scrubs names and dollar amounts before sending to the model, and re-hydrates the response — full productivity, zero data leakage.
Every API call is tagged by Department, Project, and User. Your CFO sees exactly: “Marketing spent $400 on GPT-4o for ad copy, Engineering spent $1,200 on Claude for code refactoring.” Data-driven AI budget allocation, not guesswork.
The Agentic AI monitors latency and availability across all connected models. If OpenAI is lagging, the Gateway autonomously routes to Gemini or Llama to ensure business continuity — no broken workflows, no downtime.
Real-time PII detection and redaction across every AI request. Customer names, financial figures, and proprietary code are scrubbed before leaving your network — then re-hydrated in responses your employees see.
Chargeback-ready spend tracking by department, project, and individual user. Know exactly where every AI dollar goes — from the $50 intern experiment to the $5,000 engineering pipeline.
Automatic routing across OpenAI, Anthropic, Google, and open-source models. If one provider goes down or slows, the Gateway switches seamlessly — your teams never notice the difference.
Identify when employees use unauthorized AI tools outside the Gateway. Get real-time alerts on unsanctioned usage and gently redirect users to the secure, governed pathway.
Every prompt, every response, every redaction — logged with timestamps, user identity, and department tags. Generate SOC 2, HIPAA, and GDPR compliance reports with one click.
Track which prompts are most effective across your organization. Surface “Best Practice” prompts and share them company-wide — turning your top AI users into force multipliers.
We had no idea how much sensitive data was leaving our network through AI tools until we deployed Kansoforce. In the first week, the Gateway redacted over 2,000 PII instances that would have been sent to public models. Our AI spend dropped 34% through intelligent routing, and for the first time, our compliance team can actually prove we're governing AI usage. It went from our biggest risk to our biggest competitive advantage.
Trusted by Enterprise Security Teams
Your custom playbook covers every aspect of securing AI usage, controlling spend, and maintaining compliance across your organization
We map every AI tool, API key, and shadow usage pattern across your organization — identifying where data leaves your network and who's responsible.
We configure PII detection and redaction policies tailored to your industry — HIPAA for healthcare, PCI-DSS for finance, custom rules for proprietary data.
We design chargeback workflows that tag every API call by department, project, and user — giving finance complete visibility into AI spend.
Deep profiles of your AI stakeholders — CISOs, CFOs, engineering leads, and end users — with their concerns, workflows, and adoption triggers.
Smart alerts for data leakage attempts, spend thresholds, model outages, and unauthorized AI usage — delivered via email, Slack, or PagerDuty.
Model routing policies based on task type, cost optimization, latency requirements, and provider availability — with automatic failover logic.
We work with you to audit your AI usage patterns, map data flows, and prioritize the highest-risk governance gaps
We scan network traffic, browser extensions, and API logs to identify every unauthorized AI tool your employees are using — and quantify the data exposure risk.
Every AI request is traced from user to model and back, showing exactly what data leaves your network, where it goes, and whether it was properly redacted.
Each department and user receives an AI risk score based on usage patterns, data sensitivity, and compliance posture — so you can prioritize governance where it matters most.
We create detailed profiles of 3 key stakeholders with their concerns, priorities, and the governance capabilities that drive adoption
Has zero visibility into what data employees share with AI tools. Can't prove AI compliance to auditors or regulators. Knows banning AI entirely will just drive usage underground. Needs a 'security score' dashboard with real-time redaction metrics.
Receives a single massive AI bill with no breakdown by team or project. Can't determine ROI of AI spend per department. When the CFO sees granular cost attribution, AI spend becomes a manageable line item, not a black hole.
Fears governance will add latency or block productive AI usage. Needs model flexibility — different tasks require different LLMs. When the Gateway adds <50ms latency and supports every major LLM via a single API endpoint, engineering gets governance that actually helps.
{{field_count}} sensitive fields redacted. Original prompt contained: customer names, financial figures, account numbers. All data scrubbed before reaching {{model_name}}.
Total requests: {{total_requests}}. PII redactions: {{redaction_count}}. Total AI spend: ${{total_spend}}. Cost savings from routing: ${{savings}}.
“When any request contains customer names, email addresses, phone numbers, or Social Security numbers — detect and replace with synthetic tokens before forwarding to the LLM.”
“When financial data including dollar amounts, account numbers, or transaction details is detected — scrub all monetary values and replace with anonymized placeholders.”
“Apply re-hydration rules to map synthetic tokens back to real values in responses — so employees see complete, accurate information without data ever leaving the network.”
“Route code tasks to Claude, creative tasks to GPT-4o, simple queries to open-source models — optimizing cost and quality for each task type.”
“When provider latency exceeds 500ms, automatically failover to the next-best model — ensuring zero downtime for business-critical AI workflows.”
“Enforce budget caps per department with graceful degradation — when a team hits its monthly limit, route to smaller, cost-optimized models instead of blocking entirely.”
Blocking drives AI usage underground. Employees will use personal devices, VPNs, or consumer accounts. Kansoforce gives them a governed pathway that's actually easier to use than the workarounds — so shadow AI disappears naturally.
Purview is powerful for the Microsoft ecosystem, but it can't govern Claude, Gemini, Llama, or custom models. Kansoforce is model-agnostic — one gateway for every LLM, with real-time redaction that works across all providers.
The Gateway adds less than 50ms of latency — imperceptible to users. And the automatic failover actually speeds things up: when one model lags, the Gateway routes to a faster alternative before anyone notices.
Most companies don't know their real AI spend because it's scattered across personal API keys, team accounts, and shadow tools. Our audit typically reveals 2-3x more spend than expected. The Gateway pays for itself by consolidating and optimizing.
Kansoforce is SOC 2 Type II certified, HIPAA-compliant, and can be deployed on-premises or in your private cloud. Your data never touches our infrastructure — the Gateway runs inside your security perimeter.
The Gateway uses multi-layer detection: NLP entity recognition, regex pattern matching, and context-aware AI analysis. Confidence scores determine whether to auto-redact, flag for review, or block entirely. False negative rates are below 0.3%.
A comprehensive, enterprise-ready document covering every aspect of securing AI usage, controlling spend, and maintaining compliance across your organization.
Your playbook includes an AI usage audit, shadow AI discovery, data flow mapping, PII redaction policy configuration, cost attribution and chargeback setup, model routing and failover rules, stakeholder personas, alert sequences, objection handling scripts, and ongoing governance optimization. It's a complete system for enterprise AI security.
Most deployments are live within the first week. We start with an AI usage audit, configure redaction and routing policies, connect your LLM providers, and activate monitoring. Your security team sees the dashboard from day one.
Any organization with 50+ employees using AI tools — especially in regulated industries like finance, healthcare, legal, and government. If your employees use ChatGPT, Copilot, or any LLM and you can't see what data they're sharing, you need this.
Firewalls are binary — block or allow. Kansoforce enables AI securely. Employees get full productivity while the Gateway redacts sensitive data, tracks spend, and maintains an audit trail. Blocking AI drives usage underground; governing it makes it safe.
Yes. Kansoforce can be deployed in your private cloud, on-premises, or as a managed SaaS. For regulated industries, we offer deployment options where your data never leaves your security perimeter. All options include the same full feature set.
An AI Security Trust Gateway is an enterprise-grade security layer that sits between your users and AI models. It provides prompt injection protection, PII masking, audit logging, and policy enforcement to ensure safe, compliant AI deployments.
The gateway analyzes all inputs using multi-layered detection — pattern matching, semantic analysis, and behavioral scoring — to identify and block prompt injection attempts before they reach the underlying AI model.
Yes. The gateway provides explainability logs, bias monitoring, model transparency reports, and audit trails required by the EU AI Act. It also supports GDPR data handling requirements for AI workloads.
The gateway is model-agnostic and works with OpenAI, Anthropic Claude, Google Gemini, open-source models, and custom fine-tuned models. Deploy it in front of any LLM API endpoint.
The gateway automatically detects and redacts personally identifiable information — names, emails, phone numbers, SSNs, financial data — before it reaches the AI model, then re-hydrates responses with original data for the authorized user.
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