AI Workflow
AI Workflow: ReAct Agentic Architecture, Integrations, and Forms
A Modern Approach: ReAct – Reasoning, Action, and Real Results
The ai12z platform is built on a next-generation ReAct agentic workflow—centered on a powerful Reasoning Engine that does more than just answer questions. It plans, takes action, and orchestrates the entire customer journey, drawing from your content, your systems, and real-time context.
When a user engages (with a question, search, or image), ai12z’s Reasoning Engine (LLM) receives a system prompt packed with:
- A dynamic list of available integrations, tools, and forms
- The full history and context of the conversation
- Relevant metadata (language, geo, URL, user attributes)
- Business goals and any constraints set in the prompt
The magic: The Reasoning Engine creates a plan—which may involve calling multiple integrations or forms in sequence, asking clarifying questions, or combining live and historical data—to achieve the user’s goal. Plans can adapt in real-time, even as the conversation evolves.
Integrations: Connecting Content, Data, and Actions
ai12z brings your ecosystem to life—connecting with CMS, CRM, DXP, inventory, scheduling, and virtually any third-party service via:
- MCP Protocol (Model Context Protocol)
- GraphQL & REST APIs
- Out-of-the-box connectors for 5,000+ systems
Your assistant doesn’t just answer questions—it books, updates, checks inventory, pulls reports, and more.
RAG: Retrieval-Augmented Generation as Just Another Agent
In ai12z, RAG (Retrieval-Augmented Generation) is not the end-game—it’s just one of many tools the Reasoning Engine can deploy.
- If no integration has the answer, the ReAct workflow hands off to RAG to find relevant info from your connected docs, sites, assets, and knowledge bases.
- RAG can work in parallel with other agents—think side-by-side product comparisons, collecting answers from multiple sources, or combining live API data with your proprietary knowledge.
Result: Every query gets the best, most relevant response—no dead ends, no rigid scripts.
Why ReAct and ai12z Beat Traditional Bot Frameworks
- Traditional bots rely on scripts and intent trees: rigid, high-maintenance, and easily outgrown.
- ai12z Agents are adaptive: using live context, continuous learning, and dynamic integration to deliver relevant, brand-safe answers—every time.
Key Differences:
- Adaptive, real-time conversations: Not tied to scripts, responds naturally and intelligently
- Integrated with all your content: No manual retraining for new info
- Seamless actions: Can complete tasks, not just answer
- Low-code, fast deployment: Business users and devs can launch and optimize in days
Deep Dive: How it Works
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User Input: Users ask a question (text, voice, or image). The system can process text, understand uploaded images, and personalize responses using real-time context (location, language, etc).
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Planning & Orchestration: The Reasoning Engine reviews available tools, integrations, and forms, and creates a step-by-step plan—possibly involving multiple agents (including RAG), API calls, and custom business logic.
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Search & Retrieval: For knowledge-based questions, the system queries the Vector Database (storing text, embeddings, and metadata) to retrieve and rank the most relevant info.
Inside the Vector DB:
- Embeddings: Numeric vector representations for rapid semantic search
- Text: Source snippets
- Metadata: URL, page title, tags, images, and more
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Answer Generation: The results from RAG and other integrations are used to build a final system prompt, which the Answer AI LLM uses to craft a complete, context-aware response.
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Rich Interactions & Forms: Output isn’t just a text bubble—ai12z supports branded forms, CTAs, and dynamic UI controls (validation fields, date pickers, sliders, file/image upload, and more), making it easy to collect info and guide users to take action.
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Continuous Optimization: Built-in analytics, logs, and diagnostics empower you to optimize performance, tune prompts, and ensure the assistant always puts your brand’s best foot forward.
Dynamic System Prompts & Tokens
To maximize relevance, ai12z supports dynamic tokens in prompts, allowing the assistant to reference:
{query}
– The latest user question{vector-query}
– Context-optimized version of the question{history}
– Past conversation threads{language}
,{geo}
,{origin}
– Key user/session data{attributes}
– Custom JS attributes for deeper personalization{org_name}
,{purpose}
– For tailoring brand tone and objectives- ...and more
In Summary
ai12z’s ReAct agentic workflow is a step change from yesterday’s chatbots. It orchestrates, reasons, and acts—drawing on your content, your data, and your goals. The result? A branded digital experience that’s as helpful and dynamic as your best team member.
Ready to power up your digital journey? See how ai12z can transform your customer experience—let’s get started!