The AI Agent Management Platform for CX and Operations Teams

Agent Designer gives CX, operations, and product teams a unified workspace to analyze performance, refine knowledge, tune behavior, and validate agent changes before they reach customers, all without waiting on engineering. It brings analytics, testing, guardrails, and continuous improvement together on one platform so enterprise AI agents stay accurate, predictable, and aligned to policy at scale.

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Trusted by leading companies in the Industry

Why CX and Operations Leaders Choose Agent Designer

Enterprise AI Agent Use Cases

Fintech

SaaS

Man sitting on a couch, examining a neon green piece of clothing with a curious expression next to an open cardboard box.

“The agent escalates too quickly.”

Agent Designer surfaces the reasoning behind each escalation and shows where context was misread, so teams can adjust the prompts and validate the new behavior before releasing it.

Hand reaching for a smartphone on a wooden table with a call labeled Fraud Prevention on its screen.

Fintech

“Our policy changed this morning.”

Agent Designer tests scenarios against the new rules, flags responses that break policy, and compares outputs to human agent guidance on the updated policy to produce suggested knowledge updates for review. Teams retest and confirm accuracy before customers see the change.

Two women looking at a smartphone, one wearing a white sunhat and red patterned dress, the other leaning in excitedly.

SaaS

“Customers keep asking about functionality we don’t support.”

Agent Designer analyzes these conversations, identifies the topics driving confusion, and drafts new knowledge for review based on human agent responses.

How Agent Designer Helps Enterprise Teams Configure, Test, and Improve AI Agents

Agent Designer gives enterprises a unified way to analyze performance, refine logic, and validate changes before they reach customers.

Agent Designer dashboard showing last 30 days summary with 86% resolution rate, 43% deflection rate, predicted NPS of +48, and positive sentiment with a quality trend graph.

AI Agent Performance Analytics: Resolution, Deflection, and NPS

Clear, executive ready metrics show where automation is performing and where it needs improvement.

Resolution, deflection, predicted NPS, sentiment
Strengths and issues across channels
Behavior patterns affecting quality

Ask Maven: Natural Language Analytics for Agent Performance"

Ask Maven turns natural language questions into charts, summaries, trends, and draft content so teams can explore issues without manual analysis.

Explore conversation trends
Cluster issues from uploaded files
Generate insights and summaries instantly

Diagram showing detection of conflicting, newer, and missing information feeding into a process that leads to guided updates with edits from real conversations.

Automated Knowledge Gap Detection for AI Agents

Designer surfaces outdated, conflicting or missing information based on real conversations so teams can update knowledge as products and policies evolve.

Identify gaps tied to live customer scenarios
Update content with guided suggestions
Maintain consistent structured knowledge across teams.

Centralized AI Agent Behavior Controls and Guardrails

One control layer governs tone, guardrails, escalation patterns, and system permissions.

Adjust instructions and behavioral rules
Manage which systems agents can act in
Ensure consistent behavior across all channels

Customer asks about upgrading subscription plan, AI suggests two plans: Professional $50/month and Enterprise $75/month, with a checklist of changes to validate before customers see them including policy compliance, pricing rules, edge cases, eligibility, billing, and escalations.

Regression Testing and Simulation Before Agent Deployment

Preview decisions in realistic scenarios and run regression tests across high value workflows.

Simulate conversations with custom conditions
Test complex interactions at scale
Confirm expected behavior after each change

Continuous AI Agent Improvement Through Real Interaction Data

Designer monitors real interactions to catch drift, unexpected decisions, or new opportunities.

Track feedback and behavioral trends
Detect regressions early
Iterate frequently with real time visibility

Flowchart showing continuous performance improvement with three steps: Monitor real interactions, Detect drift regressions, and Iterate & improve, connected in a cycle with a central AI icon.

Flowchart showing an Analytics Platform with two main branches: Actions to execute tasks across systems, including Pull Account Details and Submit a Refund; and Triggers to respond to system events, including Send New Conversations to Data Warehouse and Route Low CSAT to Analytics Platform.

Extend agent behavior quickly and consistently

Build and deploy custom actions and triggers directly in Agent Designer without waiting for engineering sprints. Technical teams can write capability code, test it in place, and connect agents to any system or workflow their business needs.

Build and extend agent capabilities without lengthy development cycles
Test actions and triggers directly in Agent Designer before going live
Connect agents to any system, API, or workflow your business runs on

Seamless Integration
with Maven

Explore all integrations

Training our old chatbot to respond to different support scenarios took hundreds of hours. Maven learned the answers from the moment it integrated with our systems.

Anthony Skilton

Operations and Systems Manager

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Maven’s ability to give our customers highly curated answers 24/7 is absolutely huge for us. Now, they get better, faster support, and our team has time back for high-touch tickets.

Tara Clark

Senior Client Support Manager

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Customer support is often a tradeoff between quality, speed, and cost. But with Maven, we don’t have to compromise. We can give our customers the very best support while keeping our team lean.

Jeff Ho

VP of Operations

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Just one week into the trial, rep solves per hour increased 25%. With increased efficiency on reactive operational support, we can invest more heavily in the proactive retention dollar activities.

David Doyle

Head of Customer Support

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I initially thought the main benefit would be efficiency—fewer associates, faster ticket resolution. And while that happened, the overall impact was much bigger. The quality of our tickets improved significantly.

Stas Johnson-Chyzhykov

SVP, Customer Experience

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Maven AGI autonomously handles 90% of incoming queries allowing our support agents to focus on strategic initiatives, enhancing operational efficiency and customer satisfaction.