- Visual no-code builder for business users
- Full Python SDK for engineering teams
- 50+ pre-built action blocks
- Multi-agent orchestration · Model Hub · RAG engine · Governance
Everything You Need to Build Production AI Agents
AI Hive gives every team the right tool for building AI agents in production. Business analysts use the drag-and-drop canvas. Engineers use the Python SDK. Both produce the same production-grade, governed, auditable agents — running on the same security infrastructure, observable through the same analytics dashboard.
Agent Studio: Visual Workflow Builder
Drag-and-drop canvas with 50+ action blocks. Build multi-step AI workflows visually — no code required for most use cases. Every action block is independently configurable and connects to any enabled integration. Switch to Python code view at any point; the same workflow renders as clean, exportable Python.
50+ action blocks
LLM call, API request, conditional branch, data transform, loop, delay, human-review gate, notification send, database write
Proactive engagement triggers
event-based, schedule-based, and threshold-based agent activation
Prompt IDE
write and version prompts, run A/B tests against live traffic, compare outputs across model versions
AI-assisted design
paste a natural language description, receive a first-draft workflow to edit and deploy
Multi-Agent Orchestration for Complex Enterprise Workflows
Real enterprise workflows require multiple specialised agents working in concert. AI Hive’s orchestration layer — derived from real production deployments, not research papers — provides supervisor-agent delegation, parallel task execution, shared memory, and dynamic routing. Agents coordinate without human oversight unless a human-review gate is explicitly configured.
Supervisor agents delegate sub
Supervisor agents delegate sub-tasks to specialised agents based on real-time context and task type
Parallel execution
run multiple agents simultaneously, merge outputs with configurable resolution logic
Shared memory
agents share session state, retrieved facts, and interim results across the workflow
Dynamic routing
route to the most capable agent for the current task — not just the pre-defined next step
Human-in-the-loop gates
pause any step for human review or approval before the agent continues
Model-agnostic
no pricing premium, no lock-in, no performance caps based on provider preference
Voice stack
Deepgram for speech-to-text, ElevenLabs for text-to-speech — full voice agent without a third-party voice platform
Local LLM
Llama 3, Mistral, Deepseek R1 deployable on your own GPU infrastructure — zero per-token API cost, complete data sovereignty
Every Major AI Model. Switchable Per Agent.
Every agent runs its own model assignment. Change a model, test the impact in A/B mode, and promote the winner — without touching the agent logic. BYOM supports any model exposing an OpenAI-compatible API endpoint, including fine-tuned or proprietary models running on your own GPU hardware.
RAG & Knowledge Engine: Agents That Know Your Business
AI agents are only as useful as the knowledge they can access. AI Hive’s RAG (Retrieval-Augmented Generation) engine connects agents to your enterprise knowledge — websites, documents, CRM records, ERP data — using vector search and semantic memory. Agents retrieve the most relevant information at the moment they need it, not from a static training snapshot.
Ingest from
websites, PDFs, Word/Excel docs, SharePoint, Google Drive, Amazon S3, CRM records, ERP data, SQL/NoSQL databases
Vector search
semantic similarity retrieval across any ingested content — no keyword matching required
Semantic memory
short-term memory for session context, long-term memory for cross-session learning per user or account
Automatic re-indexing
When source documents update — agents always answer from current information
PII-aware ingestion
PII detected and masked before any content is stored in the knowledge index
Deploy Agents Across Every Channel
The same agent logic runs across every channel simultaneously — chat, voice, mobile, web, social, API, and CRM. No per-channel rebuild. No separate models. One agent configuration, deployed everywhere your customers and employees already are.
Chat
Embeddable widget, configurable branding, supports text, files, images, structured forms
Voice
Full STT/TTS stack via Deepgram and ElevenLabs, IVR replacement, escalation to live agent with transcript handoff
Mobile
Native SDK for iOS and Android, push notification triggers, offline-capable fallback responses
BaaS
AI Hive as a backend-as-a-service for custom front-end apps — REST API for all agent operations
Social
Facebook Messenger, TikTok chat, WhatsApp Business API — same agent logic, channel-appropriate formatting
100+ Enterprise Integrations. Pre-Built and Production-Tested
Every integration in the catalogue has been built and tested against real enterprise systems — not demo environments. Authentication supports OAuth 2.0, API keys, and SSO. Bi-directional sync. Field-level permission controls. Every integration action logged in the immutable audit trail
Built for Engineers Too
REST API
Full OpenAPI 3.0 spec, OAuth 2.0, API key management, rate limit dashboard
SDKs
Pip install aihive-sdk (Python), npm install @aihive/sdk (Node.js), Maven artifact for Java — all with typed method signatures and full documentation
CI/CD
GitHub Actions and GitLab CI integration. Automated regression tests on pull request. Environment promotion workflow
Testing
Unit tests for individual action blocks, integration tests against sandbox environments, load testing tools, Conversation Replay for production debugging
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