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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.

ai12z AI workflow block diagram

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​

  1. 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).

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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!