Intercom, Zendesk, and Freshdesk all automate first and surface accuracy problems later — when customers report them. FortiVault reverses that. FortiAgent resolves support queries using your knowledge and live connector data. FortiVault checks whether the AI's current accuracy in that category meets your threshold before the response is sent.
Billing queries gate at 90%+. Returns at 90%+. FAQ and shipping at lower thresholds where the cost of an error is lower. Every threshold is yours to configure. Every response that falls below is held for human review — not sent to the customer.
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The Problem
Enterprise support teams adopting AI face a consistent pattern: they deploy an AI agent, volumes drop, and within weeks the first billing error or incorrect refund reaches a customer. By the time the team investigates, the automation has been running at scale for days without oversight.
The root cause is structural. Most AI customer support tools are built to automate as broadly as possible. They have no mechanism for measuring accuracy per category, no policy layer that enforces review thresholds, and no audit trail that tells you what happened after the fact.
FortiVault closes that gap. Accuracy is measured continuously. Policy is enforced before responses are sent. Every decision is logged. And when errors occur, the audit trail tells you exactly what happened.
The Platform
FortiVault is a two-layer enterprise AI customer support platform. FortiAgent is the execution layer. FortiVault is the governance layer. Together they give you AI support that scales without losing control.
FortiAgent resolves customer support queries using grounded knowledge and live connector data. It does not operate on general model knowledge or generate responses from training data alone. Every response is sourced from your explicitly configured knowledge base — your FAQs, your policies, your product documentation — and enriched with live data from your connected systems.
FortiVault sits above FortiAgent and governs every decision before a response is sent. It measures AI accuracy continuously, enforces automation policy per support category, and logs a full audit trail for every decision — whether automated or reviewed.
How It Works
Every query follows a structured flow through the platform. FortiAgent handles execution. FortiVault governs each decision before the customer sees the response.
Via the FortiAgent widget or a connected support channel.
Knowledge sources searched. Registered connector APIs called if real-time data is needed.
Grounded in your configured knowledge and live connector results — not general model knowledge.
AI Trust Score computed. Automation gate threshold checked for this support category.
If accuracy meets the threshold, the response is sent. If not, it enters the human review queue.
Human overrides and audit data refine the Trust Score, expanding safe automation over time.
Platform Features
Trust Score, automation gating, audit trail, live connectors, human review, and guidance rules — built into one coherent governed support stack.
A continuously updated accuracy signal per support category — based on real conversation outcomes, human override rate, and connector reliability. Tells you exactly which categories FortiAgent is ready to automate and which still require oversight.
Billing, returns, login, technical support — each has its own accuracy threshold. Automation is enabled only when measured accuracy meets the gate for that specific category. Thresholds are configurable and reversible at any time.
Every AI decision is logged: knowledge source used, connector call made, guidance rule applied, and outcome recorded. Every response is traceable to its source. No black-box outputs.
FortiAgent connects to Shopify, Stripe, Zendesk, and Salesforce to retrieve live data at query time. Order status, subscription details, account information — answers reflect real-time system state, not static knowledge content.
Responses that fail the automation gate route to your team before the customer sees them. Reviewers approve, edit, or reject. Corrections are logged and feed the accuracy model. The queue shrinks as Trust Score improves.
Tone, compliance constraints, and escalation conditions are defined explicitly in configuration. All agent behaviour is auditable — not emergent. Configuration-time decisions, not runtime surprises.
Why Governance Matters
Scaling AI support without a governance layer is operationally manageable in low-stakes categories — shipping status lookups, FAQ answers, basic product information. It becomes a liability the moment AI is handling billing queries, refund decisions, account changes, or anything that touches a customer's financial relationship with your business.
Without governance, you cannot measure whether AI accuracy in billing queries is above or below a safe threshold. You have no mechanism to require human review in categories where errors are high-stakes. You have no audit record when a customer disputes an AI-generated response.
You find out automation is failing when errors reach customers — not before. FortiVault makes that structural, not reactive.
Without FortiVault
With FortiVault
Built For
FortiVault is a fit for support operations where accuracy matters before scale, and where a black-box AI decision is not something the business can accept.
Handling thousands of return, refund, and billing queries daily. A 5% billing error rate is survivable at 200 queries — it is 250 wrong answers a day at 5,000. FortiVault's gates prevent that from multiplying freely.
Account cancellations, subscription changes, and billing disputes processed by AI need explicit write-back procedures and accuracy gates. An AI that confidently processes the wrong cancellation is worse than no AI at all.
Regulators expect explainable AI decisions in customer-facing finance. FortiVault's per-decision audit trail — knowledge source, connector call, rule applied, outcome — gives compliance teams the record they need.
IT teams that need to sign off on AI in customer-facing workflows need to see a measurable policy layer — not just a deployment plan. FortiVault's Trust Score and gating configuration is that layer.
FAQ
No. FortiVault and FortiAgent work alongside your existing helpdesk. FortiAgent connects to Zendesk and Salesforce as live data connectors. FortiVault adds a governance and oversight layer above your AI support operation — it does not replace your ticketing system.
The Trust Score is a continuously updated accuracy signal calculated from real conversation outcomes in your support environment. It aggregates response accuracy, human override rate, connector reliability, and escalation rate — calculated independently per support category. It reflects FortiAgent's actual performance in your specific operation, not a generic confidence estimate.
FortiVault routes every response in that category to the human review queue. Your support team reviews, edits if necessary, and sends. The override is logged and the Trust Score updates to reflect the correction. Automation is re-enabled when accuracy recovers above the threshold.
No. FortiAgent responds only from your configured knowledge sources — FAQs, policies, and product documentation. Connector calls retrieve live data from your registered systems. There is no fallback to general model training knowledge, which means no hallucinated policies and no training data leaking through.
Yes. The recommended deployment approach is to start with all categories in review mode, collect accuracy data, and unlock automation category by category as the Trust Score reaches your configured thresholds.
Explore the Platform
AI Governance Layer
Trust Score, automation gating, and audit trail in depth
FortiAgent
AI support execution layer — knowledge, connectors, procedures
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