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Overview

GIDR.ai is an agentic orchestration platform for designing, deploying, and operating intelligent AI systems that execute real work across enterprise workflows. The platform combines conversational AI, deterministic automation, multimodal intelligence, and full operational governance into a single system of action. It’s core runtime and orchestration layer manages how AI agents reason, act, integrate with enterprise systems, and produce auditable outcomes. It provides secure execution, scalability, observability, and governance across all deployed use cases. It acts as a system of action rather than a passive chatbot platform. Agents can invoke tools, query systems, validate inputs, trigger workflows.

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GIDRs (Use Cases)

A GIDR represents a deployed business use case built on the platform. Each GIDR encapsulates:

• A specific workflow or operational objective
• One or more AI agents
• Integrated tools and data sources
• Business rules, safety gates, and policies
• Analytics and audit visibility

Examples include service automation, customer support agents, technician guided procedures, inspe assistants, compliance workflows, etc. GIDRs can be iterated rapidly while maintaining production controls.

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GIDETs (AI Agents)

GIDETs are autonomous reasoning entities that execute tasks within a GIDR. GIDETs can understand intent, retrieve knowledge, invoke tools, make decisions, and collaborate with other GIDETs. Each GIDET may include:

• Reasoning logic using ReAct or deterministic flows
• Tool access via MCP and REST integrations
• Conversational multimodal input and output such as voice, text, and vision
• Memory and context management
• Safety constraints and validation

GIDETs operate under orchestration rather than freeform prompting, enabling predictable and auditable behavior.

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AI Studio

AI Studio is the low code and no code environment used to design, configure, test, and deploy GIDRs and GIDETs. Key capabilities include:

• Visual flow builder with Start and End nodes
• Safety gates and conditional routing
• Tool invocation and API orchestration
• Direct database read and write access with governed permissions
• Model selection and rapid experimentation
• Live testing and debugging
• Publishing

Studio allows teams to move from prototype to production without rewriting systems code.

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MCP Tool Ecosystem

The Model Context Protocol (MCP) enables AI agents to securely discover and invoke tools across internal systems, SaaS platforms, databases, and APIs. Tools may include:

• CRM and ticketing systems
• Databases and analytics services
• Knowledge systems and vector stores
• Custom enterprise APIs
• Automation workflows

MCP standardizes tool publishing, permissions, observability, and reuse across agents.

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Data sources

The Data sources provides structured and unstructured retrieval for agents. It supports hybrid search using vector embeddings and structured queries. Capabilities include:

• Document ingestion and chunking
• Metadata enrichment and filtering
• Semantic retrieval and reranking

This ensures agents deliver accurate, grounded responses and decisions.

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Conversational & Multimodal Interaction

GIDR enables natural conversational interaction across voice, text, images, and sensor inputs, allowing users and systems to engage with AI agents fluidly in real operational environments. This enables:

• Natural conversational voice and text interactions
• Visual verification and inspection workflows
• Image based recognition and validation
• Hybrid human AI collaboration across modalities

Conversational multimodal capabilities allow agents to operate seamlessly across digital and physical workflows.

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Analytics and Insights

GIDR transforms operational activity into measurable business intelligence. Dashboards support:

• KPI tracking such as AHT, FTR, ROI
• Trend analysis and benchmarking
• Workflow bottleneck identification
• Agent performance monitoring
• Compliance reporting

Analytics connects AI execution directly to business outcomes.

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