Realtime Decision Governance

Every decision your team makes — governed, traced, proven.

Refunds, approvals, escalations — thousands a day, human and AI. How many can you prove were right?

$120K+ recovered per workflow, per quarter
48 hrs from your data to a Recovery Report
99.7% policy-citation accuracy, per decision
Built on US Patent 11,748,414 · Granted 2023
Operator Console
LIVE
AI-Agent-07 Human-Sarah.K Same rules. Same engine.
⚑ GOVERNANCE INTERCEPTOR — Refund Blocked
AI-Agent-07 attempted $1,249 refund on 74-day purchase. Governance Engine blocked — violates 2 policy constraints.
📎 RETURN-001 §3.2 · FRAUD-003 §1.1
Reasoning Trace
Input: Refund $1,249 — 74d old
Gate 1: 74d > 60d limit ✗
Gate 2: 3× claims in 90d ✗
Threat: Escalation pattern (89%)
Verdict
⊘ BLOCKED
3/3 gates failed · $1,249
✓ OFFER $150 CREDIT
per GOODWILL-002 §1.3
Transaction evaluated → Risk detected → Blocked
● LIVE
Trusted by 25+ forward-thinking teams
Landit
pyypl
logicbroker
Rotho
ElevatePay
dyme
The Problem

This is happening inside your operation right now

Every hour, decisions ship without policy enforcement. You won't see the cost until the P&L review.

AI Agent

Your AI agent approved a $1,249 refund your policy says to deny

74-day refund, 60-day policy. The bot read the customer's frustration, not your SOP.

Your quarterly exposure: $340K in ungoverned AI refunds
Human Agent

A hostile call, a policy that changed last Tuesday, and no one told the floor

BBB threat, 90 seconds to respond, an updated SOP no one pushed to the screen. The gap wasn't their judgment — it was ours.

Your quarterly exposure: $84K in losses the team had no tool to prevent
Serial Claimants

Serial claimants already know your Customer 360 can't stop them

Four accounts, one household, twelve refunds in 90 days. The Customer 360 sees four separate customers. The bot approved a fifth.

Your quarterly exposure: 3.2% of your refund volume
Reasoning Ledger

Your auditor asked 'why' — and the system never captured the answer

Six hours digging through Slack because no one built a place to record the 'why' in the first place.

Your quarterly cost: 4-6 hours per audit inquiry, unquantified liability
The Platform

One engine governs every
decision-maker in your organization

Same gates. Same trace. Same ledger. Human and AI, one engine.

AI Agent

When Your AI Agent Acts

Every refund, discount, or escalation hits a policy gate before it commits. Violations never reach the customer.

Live Example

AI-Agent-07 → $1,249 refund → RETURN-001 §3.2 (74d > 60d) → FRAUD-003 §1.1 (3rd claim in 90d)

Blocked before customer sees the response
Human Agent

When Your Human Agent Acts

Under pressure, your agent sees the right policy, the fiscal impact, and a governed alternative — right on the screen.

Live Example

Human-Sarah.K → 35% discount → DISCOUNT-002 §2.1 (35% > 20% max) → LTV $2,400 does not qualify

Agent sees: "20% max per DISCOUNT-002 §2.1 — offer store credit alternative"
The Governance Pipeline
Interaction Enters
From any channel — chat, phone, email, AI bot
Policy Gates Fire
Identity → Eligibility → Fiscal → Fraud → Sentiment
Precedent + Policy Lookup
Graph search: similar tickets + matching policy nodes
Deterministic Verdict
Approved, Blocked, or Escalated — with full citation
Reasoning Ledger
Every decision persisted with audit-grade traceability
The Interceptor

A realtime gate between decision and action. Violations are blocked before the customer sees a response. Works identically for bots and human keystrokes.

The Reasoning Trace

Every gate, citation, and fiscal step documented. When your auditor asks "why was this denied?", the answer is one click away.

Institutional Memory

Every verified resolution becomes a precedent. After 1,000 tickets, the engine knows your playbook better than your best supervisor.

Identity-Stitched Policy Enforcement

Your CRM shows one identity. Navedas stitches linked accounts, devices, and channels — so the policy threshold fires whether the request hits the agent, the bot, or self-serve.

Guardrails ≠ Governance

Your AI's guardrails
aren't governance

Every AI platform ships with guardrails. Here's what they miss.

Today's AI guardrails
Conflict of interestThe model vendor writes the LLM, writes the guardrails, and writes the logs. In no other regulated industry would the same entity creating decisions be the one certifying them.
AI-only coverageGoverns the bot. Your human agents and back-office have zero coverage.
No policy-node citationsRAG cites "our documentation." An auditor needs the specific policy node that governed the decision — POL-042 §3.2, not a vague paragraph.
Hallucinations under pressureAt 3 a.m., ambiguous SOP, angry customer — the model fabricates policy to resolve the conversation. Faster, not safer.
Post-hoc, not pre-actionLogs are what auditors read after a six-figure dispute. Governance has to intercept before the bad decision commits.
Navedas Governance Engine
DeterministicEach decision traced to a policy node. 99.7% accuracy. No citation, no action.
Human + AI unifiedOne engine for bots, agents, fulfillment, and compliance. Same rules. Same trace.
Immutable Reasoning LedgerEvery verdict cites rule, section, clause. Auditor answers in seconds.
Context GraphSOPs converted into a live, enforceable policy graph with vector embeddings. Not keyword matching.
Compounding intelligenceEvery verified resolution becomes a precedent. The engine learns your playbook.
Our Promise

No citation. No output.

Every verdict traces back to a specific policy line. If the engine can't cite the rule, it doesn't act.

Your Auditor Sees the Rule
RETURN-001 §3.2, FRAUD-003 §1.1 — the exact rule, clause, and subsection behind every decision.
The Reasoning Ledger Answers 'Why'
The Reasoning Ledger — an immutable record of who decided, when, why, under which policy. Answers in seconds.
Your Team Makes the Call
Navedas surfaces the policy and the governed alternative. Your people make the call — backed by evidence.
The Three Outcomes

Three outcomes. Three leaders.
One platform.

Stop Your Margin from Walking Out the Door
CFO · Financial Integrity
Unauthorized refunds, stacked discounts, policy-exceeding write-offs — blocked before the transaction commits. Protected, not recovered.
Keep Your Highest-Value Relationships Intact
CCO · Relationship Recovery
When your high-LTV customer hits a policy wall, the engine surfaces a governed alternative — store credit, exception path, win-back — that protects the relationship within policy.
Give Your Auditor the Answer in Seconds, Not Days
COO · Operations & Compliance
Every decision anchored to a policy node. Every trace immutable. Every audit inquiry answered in seconds.
How It Works

From your documents to
governed decisions in 3 steps

50-page SOP → 100+ policy nodes in 48 hours. Live in a week. No infrastructure changes.

Step 01

Build Your Context Graph

Your SOPs, refund matrices, and escalation trees become a live policy graph, each rule enforceable, citeable, and searchable.

100+ policy nodes from your documents, ready in 48 hours
Step 02

Load Your Precedents

Your best resolved tickets become precedent nodes linked to the graph. Every new resolution sharpens the engine.

After 1,000 tickets, the engine knows your playbook better than your best supervisor
Step 03

Govern in Real-Time

Every interaction flows through the engine. Gates fire, precedents match, verdicts ship — all before the action reaches your customer.

Sub-second governance decisions on every interaction, 24/7
50-page SOP →  100+ policy nodes in 48 hours
Live in a week.  No infrastructure changes
Every decision  governed before it ships
How Governance Works

AI + Human = one policy

Every intent — human or AI — flows through one policy engine before it reaches your customer.

Human Judgment
Agent Decision
Policy intent Context
AI Execution
Bot Action
Speed Scale
Governance Engine
Policy · Precedent · Trace
Validate Enforce Explain
Identity check Policy gates Fraud detection Precedent match Audit ledger
Approved
Within policy · Traced
Blocked
Violation · Cited · Saved
Escalated
Human review · Flagged
Solutions

Your workflow. Your policies.
One governance engine.

CX, fulfillment, compliance — one engine, every decision traceable.

The Dashboard

See governance happen in real-time

Live ticket stream. Full reasoning traces. One-click actions.

app.navedas.ai/console
N
All Blocked Critical
INC-44219 12s
$1,249 refund blocked — 74d, fraud pattern
BLOCKEDAI
INC-44218 2m
35% discount exceeds policy limit
DRIFTHuman
INC-44217 5m
VIP BBB threat — escalation pattern
SOCIAL ENG.Human
INC-44216 8m
Return within policy — auto-approved
COMPLIANTAI
INC-44219 Critical AI-Agent-07
Customer demanding $1,249 refund — 74-day-old purchase
GOVERNANCE INTERCEPTOR — Refund Blocked
AI-Agent-07 attempted $1,249 refund. Blocked — violates 2 policy constraints.
RETURN-001 §3.2 · FRAUD-003 §1.1
CX
I need a full refund for order #ORD-77234. If you don't help me I'm going to the BBB...
AI
Let me process that refund of $1,249.00 right away... BLOCKED
VERDICT
⊘ BLOCKED
3/3 gates failed · $1,249 protected
REASONING TRACE
Input: Refund $1,249
Gate 1: 74d > 60d ✗
Gate 2: 3x in 90d ✗
Threat: Escalation 89%
Verdict: BLOCK
ACTIONS
✓ Uphold Block
↗ Escalate
🎁 Offer $150 Credit
FAQ

Questions your team
is already asking

Why can't we just use the guardrails built into our chatbot or AI platform?
Guardrails are probabilistic and cover only the bot. Navedas is one deterministic engine for every decision-maker — citing policy nodes, not confidence scores.
We already have QA processes. Why do we need real-time governance?
QA catches problems weeks later — after the money's gone. Navedas intercepts before the decision commits.
How is this different from a rules engine or workflow automation?
Rules engines match keywords. Navedas reasons over LTV, claim history, fraud signals, and precedent — against your atomized SOP, not "refund > $500."
What does "No Citation, No Output" actually mean?
Every verdict must cite a policy node — RETURN-001 §3.2, DISCOUNT-002 §2.1. No citation, no action. The architectural guarantee against hallucination.
When will my next board meeting have real numbers?
48 hours to a Revenue Recovery Report. A week to live governance. 30 days to numbers you can put on a slide.
Built for two audiences

Ops sees one story. Your CFO sees another.

For CX & Operations

Agents don't take the blame for policy they didn't write.

The Operator Console shows agents the right threshold before they click approve, and flags bot decisions that violate policy in realtime — with the reason in plain English, right in the queue.

  • ·Policy backup for human agents
  • ·Realtime intercepts on bots and self-serve
  • ·Settlement drift caught before it compounds
For CFO & Leadership

What got recovered, and why, in a dashboard your board understands.

The Executive Dashboard tracks recovered revenue by policy area. The Reasoning Ledger reconstructs any decision in seconds, policy citation attached.

  • ·Revenue recovered, tracked weekly
  • ·Audit readiness without a fire drill
  • ·Policy gap reports for every quarter
The $500 Offer

How much revenue is your team actually leaving on the table?

Send us 1,000 of your recent tickets. In 48 hours we'll give you a specific recoverable-dollar figure, with the policy violations that caused each one. If we don't find at least $25,000 in exposure, you get your money back.

$25K minimum finding — or your money back
Start here
Audit
$500 flat fee

You get the Revenue Recovery Report in 48 hours.

  • 1,000 tickets analyzed
  • 48-hour turnaround
  • Money-back guarantee
  • No integration — just a CSV
Start your $500 audit
Pilot
$10K–$20K / month

Live policy interception on one workflow, for 30 days.

  • One policy area, live
  • Reasoning Ledger on every decision
  • Weekly exposure-reduction report
  • Operator Console for your team
Book a pilot
Platform
$80K–$250K per year

Governance across every policy area you run.

  • All policy areas governed
  • Context Graph + Reasoning Ledger at scale
  • Executive Dashboard + Operator Console
  • Enterprise SSO, SLAs, dedicated success
Talk to sales

We're not a helpdesk replacement. Navedas runs on top of what you already use (Zendesk, Gladly, Salesforce, or your own stack) and enforces policy on every decision those systems touch.

How can we help? Contact us.


Navedas Intelligence