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GuidrAI

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Build, deploy, and observe enterprise AI customer-service agents from one platform, using plain English.

The problem

Traditional customer service platforms force teams to choose between power and simplicity, and they treat AI as a black box with no visibility into why it responded the way it did. Businesses struggle to build agents without engineering help, keep quality consistent across channels, and enforce compliance and governance at scale.

What it is

GuidrAI is an enterprise-grade platform for building, optimizing, and scaling AI customer-service agents from one place. Non-technical users create agents and workflows by describing what they want in plain English, while technical teams retain code-level control to enforce guardrails. Every response is fully traceable, showing which model, knowledge, and workflows produced it. The same agent delivers consistent quality across chat, email, voice, SMS, and API.

Why it matters

What you get

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Natural language setup

Describe the agent or workflow you want in plain English and GuidrAI configures it for you.

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Complete transparency

See exactly why the AI made each decision, which knowledge it used, and which workflows it triggered.

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Enterprise governance

Audit trails, guardrails, and compliance controls keep sensitive operations secure and reviewable.

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True omnichannel

Deliver the same agent and same quality across chat, email, voice, SMS, and API.

Capabilities

Everything GuidrAI does

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AI agent builder

Create fully functional agents from a natural language description that auto-configures type, channels, tools, and system prompts.

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Agent operating procedures

Define custom business logic as workflows with triggers, steps, conditions, and actions. Non-technical users iterate while technical teams keep control.

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Unified knowledge graph

A single data layer with pgvector semantic search over uploaded PDFs, TXT, MD, and DOCX. Every interaction feeds continuous improvement.

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Model-agnostic LLMs

Choose Anthropic Claude or OpenAI GPT per agent, tune temperature and token limits, and fail over automatically between providers.

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Watchtower monitoring

Review, flag, and audit responses before, during, or after delivery, with sentiment alerts, escalation tracking, and compliance enforcement.

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AI-powered insights

Track conversation volume, AI handled rate, response time, and top agents across custom time ranges from 7 to 90 days.

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Transparent observability

Trace every decision with model tracking, token usage, workflow tracing, knowledge attribution, and a full reasoning audit trail.

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One-click integrations

Connect CRM, ticketing, payments, e-commerce, communication, and knowledge tools, plus custom REST, GraphQL, and webhook APIs.

How it works

From start to value

STEP 01

Build

Describe your agent and its workflows in plain English, then connect knowledge bases and the tools it needs.

STEP 02

Deploy

Launch the same agent across chat, email, voice, SMS, and API with consistent behavior everywhere.

STEP 03

Observe

Trace every response to its model, knowledge, and workflow while Watchtower flags and audits conversations.

STEP 04

Optimize

Use analytics, guardrails, and testing to close knowledge gaps and improve agent performance over time.

Use cases

Where teams use it

โœ“E-commerce teams automating product inquiries, order tracking, and returns.
โœ“SaaS companies handling technical support, onboarding, and feature education.
โœ“Healthcare providers managing appointment scheduling, basic triage, and FAQs.
โœ“Finance teams supporting account inquiries, transaction help, and fraud alerts.
โœ“Education organizations offering student support, course information, and enrollment help.

Who it's for

Enterprise customer-service and support teams that need to build governed, transparent AI agents without engineering bottlenecks.

Works with

SalesforceHubSpotZendeskJiraServiceNowStripePayPalShopifyWooCommerceSlackMicrosoft TeamsConfluenceNotionGoogle DriveSharePointAnthropic ClaudeOpenAI GPT-4opgvectorLangChain

What sets it apart

  • โ—† Plain-English setup gives non-technical users self-service agent building while technical teams keep code-level control for guardrails.
  • โ—† Full decision-level observability traces each response to its exact model, knowledge articles, and triggered workflows.
  • โ—† Model-agnostic architecture lets you switch between Anthropic and OpenAI per agent with automatic failover.
  • โ—† Watchtower auditing plus enterprise guardrails enforce compliance, PII detection, and escalation across every conversation.
FAQ

Common questions

Do I need engineering help to build an agent?

No. You can describe the agent and its workflows in plain English, and GuidrAI extracts the configuration, channels, tools, and system prompts for you, while technical teams can still refine the underlying logic.

Which LLM providers are supported?

GuidrAI is model-agnostic and supports Anthropic Claude and OpenAI GPT-4o today, with per-agent model selection, configurable limits, and automatic failover between providers.

How does GuidrAI handle compliance and oversight?

The Watchtower module lets you review, flag, and audit responses with sentiment alerts and escalation tracking, and guardrails enforce PII detection, identity verification, and compliance rules with complete audit logs.

Start building transparent, governed AI customer-service agents with GuidrAI today.

Reach out for early access, a live demo, or a partnership conversation.

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