The Trend Everyone's Talking About

On January 19, 2026, Trend Hunter published an article about Agentic AI Workflows, highlighting how companies like EverWorker are helping enterprises deploy "no-code agentic AI" to handle repetitive, rules-based tasks. The trend scored 8.2 for popularity, activity, and freshness.

The article describes a future where:

  • AI agents are configurable to handle company-specific processes
  • Integration is seamless with existing data sources
  • Deployment is incremental, not chaotic
  • No-code platforms lower the barrier to entry

Here's the thing: WRIO has been doing this since 2023.

While the industry is just waking up to the potential of agentic AI, we've been quietly building it, testing it, and deploying it for mission-critical operations. This isn't vaporware. It's not a pitch deck. It's production-grade infrastructure powering real businesses today.

What Makes AI "Agentic"?

Before diving into what we've built, let's define the term. Agentic AI refers to AI systems that:

  1. Reason independently: They analyze context, weigh options, and make decisions without human input at every step.
  2. Execute multi-step workflows: They don't just answer questions—they perform complex, sequential tasks.
  3. Adapt to exceptions: They handle edge cases, retry failures, and branch based on outcomes.
  4. Integrate with real systems: They read from databases, call APIs, send emails, and update CRMs—not just generate text.

Traditional AI tools (like ChatGPT or Gemini) are assistive—they help you think, write, and research. Agentic AI is executive—it does the work for you, start to finish.

WRIO's Agentic Architecture: What We've Built

1. Workflow Engine with State Management

Our core is a stateful workflow orchestrator that:

  • Executes BPMN-based processes (Tasks, Gateways, Events)
  • Maintains execution context across nodes
  • Handles conditional branching and exception paths
  • Logs every decision for auditability

Real-world example: When a lead submits a form on Sonar, the workflow:

  1. Validates the email via AWS SES
  2. Enriches the contact with IPinfo.io geolocation
  3. Checks if they're a B2B visitor (ASN lookup)
  4. Routes them to different sequences based on company size
  5. Sends personalized follow-ups via SendGrid
  6. Updates the CRM (D1 database) with interaction history

All of this happens without human intervention—that's agentic AI in action.

2. AI Nodes with Gemini Integration

We've integrated Google Gemini 2.0 as a reasoning layer inside workflows. Our AI nodes:

  • Extract structured data from unstructured input (e.g., "Extract company name, pain points, and urgency from this Reddit comment")
  • Generate contextual responses (e.g., "Write a personalized outreach email based on this lead's profile")
  • Classify and route (e.g., "Is this a 🔥 Hot Lead, 🤝 Partnership Opportunity, or 🎣 SEO Bait?")

Example from Forge Knowledge Ingestion: When a user uploads a document to Forge, the forge_ingest workflow:

  1. Task_GetFile: Downloads the file from R2 storage
  2. Task_GenerateZettels: Sends the content to Gemini with a structured prompt:
    • "Extract atomic knowledge units (Zettels) from this document"
    • "Each Zettel should answer: Who, What, When, Where, Why, How"
    • "Return as JSON-LD with metadata (title, tags, relationships)"
  3. Task_SaveZettels: Stores each Zettel in R2 + indexes in D1
  4. Task_UpdateKB: Links Zettels to the parent Knowledge Base

The AI doesn't just "chat"—it executes a structured pipeline with validation, retries, and error handling.

3. Process-as-a-Service (PraaS)

We've built a Forms Engine that auto-generates UI from JSON-LD schemas. This means:

  • Non-technical users can define a workflow in a .jsonld file
  • The system auto-creates the form UI (using @bpmn-io/form-js)
  • Submissions trigger workflows directly
  • Results update in real-time via Server-Sent Events (SSE)

Example: The Forge Wizard (wrio/projects/forge/processes/ingest/wizard.jsonld) defines:

  • Input fields (File Upload, Knowledge Base Name)
  • Validation rules (Required fields, file type restrictions)
  • Success/Error states (BPMN transitions)

The frontend renders this as a living form widget that anyone can embed via iframe. No React components. No custom code. Just data.

4. Hybrid Ownership Model

One of our most innovative (and complex) features is Template Inheritance. Here's how it works:

  • Global Templates (owned by wrio org): Reusable workflows like first_ping, forge_ingest, create_project
  • User Copies (owned by individuals): When a user starts a process, we copy the template to their workspace
  • Link Files: Instead of duplicating definitions, we use reference pointers that allow downstream inheritance.

This solves a critical problem: How do you update a template without breaking everyone's running workflows?

Answer: We version the templates. When we release ingest_v2, existing users stay on ingest_v1 until they explicitly upgrade. No breaking changes. No downtime.

This is exactly what the Trend Hunter article describes as "incremental, clearly scoped deployments rather than broad, sweeping transformations."

5. Data Governance & Observability

Every workflow execution is logged:

  • Who: User ID and org (e.g., @alexey-anshakov)
  • What: Process ID and step ID (e.g., forge_ingest/Task_GenerateZettels)
  • When: ISO timestamps with millisecond precision
  • Input/Output: Full JSON payloads (sanitized for PII)
  • Status: pending, running, completed, failed
  • Errors: Stack traces and retry attempts

All logs are stored in Cloudflare D1 (our SQL database) and R2 (object storage). This gives us:

  • Compliance: Full audit trails for GDPR/CCPA
  • Debugging: Replay any workflow execution
  • Analytics: Dashboard metrics (completion rate, avg execution time, failure points)

We also expose this via real-time SSE streams, so users can watch their workflows execute live (like a progress bar, but with actual reasoning steps).

The "No-Code" Myth

The Trend Hunter article emphasizes no-code as a key feature. Let me be honest: no-code is a marketing term—what you really want is low-abstraction, high-leverage code.

Here's our approach:

  • Forms: Pure JSON-LD (no TypeScript)
  • Workflows: BPMN + JSON-LD (visual editor coming soon)
  • AI Prompts: Structured templates (you fill in variables)
  • Data Models: JSON-LD schemas (like schema.org)

But under the hood? We write TypeScript, SQL, and Bash. Why? Because:

  1. Reliability: Type-safe code catches errors before production
  2. Performance: Hand-optimized queries beat drag-and-drop every time
  3. Flexibility: We can integrate anything (AWS SES, IPinfo, Gemini, BPMN.io, Cloudflare R2/D1)

The user experience is no-code. The infrastructure is bulletproof code.

The Economics: $0.47 vs $299

The hidden killer feature of WRIO isn't just intelligence—it's efficiency.

Current automation tools like Zapier charge a "tax on success." You pay per task.

  • Zapier: ~$299/mo for 50,000 tasks.
  • WRIO: You pay only for the bare metal compute you use (via Cloudflare).

For reference, processing 10,000 complex lead enrichment workflows costs us $0.47 in Cloudflare infrastructure fees. On legacy platforms, that same volume would cost hundreds of dollars.

Because our agentic workflows run on your infrastructure (Cloudflare Workers), we don't mark up the compute. We just orchestrate it. The economics are unfair by design.

Why We're 2 Years Ahead

Most companies build AI tools by duct-taping ChatGPT to a web form. We took a different path:

  1. Start with workflows, not chat: We built a stateful orchestrator first, then added AI as nodes
  2. Design for governance: Every decision is logged, auditable, and reversible
  3. Prioritize composition: Small, reusable nodes (like Unix pipes) instead of monolithic services
  4. Think in processes, not features: "Lead enrichment" isn't a feature—it's a 7-step workflow

This architecture didn't come cheap. We've rewritten the workflow engine 3 times. We've migrated databases twice. We've iterated on 10,000+ real-world executions across our internal e-commerce divisions (like our Autoparts network).

But the result? When Gemini 3.0 or GPT-6 comes out, we just swap the API key. The workflows keep running.

That's the power of abstraction.

What This Means for You

If you're reading this, you're probably:

  • An enterprise IT leader evaluating AI vendors
  • A startup founder building automation tools
  • A developer curious about agentic systems

Here's what you should take away:

For Enterprises:

You don't need to wait for "the perfect AI" to start automating. Start with rules + AI hybrid workflows:

  • Use AI for unstructured data (email classification, sentiment analysis)
  • Use rules for structured data (form validation, CRM updates)
  • Combine them in a stateful orchestrator (like WRIO)

For Founders:

Don't build "ChatGPT for X." Build workflows that solve X—and plug in ChatGPT as a node. When GPT becomes obsolete, your infrastructure survives.

For Developers:

Study state machines, event-driven architecture, and BPMN. The next wave of AI won't be "better prompts"—it'll be "better orchestrators."

Stop building AI tools. Start building AI systems.
Your competitors are already deploying agentic workflows while you're still arguing about which LLM to use.

Try WRIO Free → | See Live Demo (Forge Wizard) →

Frequently Asked Questions

What is the difference between Agentic AI and traditional automation?

Traditional automation follows fixed if-then rules: "If form submitted, send email." It breaks when the input is unexpected. Agentic AI reasons about context: "This form submission seems incomplete. Should I ask for clarification, auto-fill from previous data, or escalate to a human?" It handles exceptions without hardcoded rules, adapts to new scenarios, and can chain multiple decisions into complex workflows. Think of it as the difference between a vending machine (press button, get soda) and a personal assistant (understands your preferences, suggests alternatives, remembers your allergies).

How does WRIO ensure data privacy if AI is processing my business data?

WRIO uses on-premises execution for sensitive steps. When you run a workflow, the orchestrator runs in your Cloudflare Workers environment (not our servers). We only store metadata (timestamps, step names, success/failure status) in our D1 database. The actual data (emails, CRM records, documents) stays in your R2 bucket. For AI processing, we send data to Google Gemini via HTTPS, but you can configure self-hosted LLMs (like Llama 3) if you need air-gapped compliance. We're GDPR-ready and provide full audit logs for every API call.

Can I use WRIO with my existing CRM or database?

Yes. WRIO workflows can connect to any system via:

  1. API Calls: REST/GraphQL clients (we have nodes for fetch, axios, and Cloudflare Workers bindings)
  2. Database Queries: Direct SQL for PostgreSQL, MySQL, Cloudflare D1, or Supabase
  3. Event Webhooks: Trigger workflows from Zapier, Make, n8n, or custom webhooks
  4. File Systems: Read/write to R2, S3, Google Drive, or local storage

For popular tools (Salesforce, HubSpot, Airtable), we provide pre-built connectors (JSON-LD schemas that auto-map fields). For custom systems, you write a 10-line TypeScript node. Example: our Autoparts outreach system integrates with AWS SES (email validation), SendGrid (sending), IPinfo.io (geolocation), and a custom CSV database—all in one workflow.

Is WRIO actually "no-code" or do I need to hire developers?

Reality check: WRIO is low-code for processes, no-code for forms. Here's what you can do without coding:

  • Create forms (drag-and-drop JSON-LD builder coming Q2 2026)
  • Configure workflows (visual BPMN editor in beta)
  • Set up conditional logic (e.g., "If lead score > 80, send to sales")

What requires coding:

  • Custom integrations (if we don't have a connector yet)
  • Advanced AI prompts (we provide templates, but power users can write raw Gemini API calls)
  • Data transformations (e.g., "Convert this CSV to JSON-LD")

Think of it like WordPress: you can build a blog without code, but if you want custom plugins, hire a dev. Most clients start with our templates, then hire us for 5-10 hours of customization.

How much does WRIO cost compared to tools like Zapier or Make?

WRIO is free for developers (open beta until Q3 2026). After that:

  • Starter: $29/month (1,000 workflow executions, 10 GB storage)
  • Professional: $99/month (10,000 executions, 100 GB storage, priority support)
  • Enterprise: Custom pricing (unlimited executions, dedicated infrastructure, SLA)

Compared to Zapier ($20-$600/month for 750-50,000 "tasks"), we're cheaper per execution because our workflows run on your Cloudflare account (you only pay Cloudflare's infrastructure costs, which are ~$5/month for most SMEs). See "The Economics" section above for the breakdown.

Can WRIO replace my entire automation stack?

Probably not—and that's okay. WRIO excels at:

  • Complex, multi-step workflows (e.g., lead qualification → enrichment → outreach → follow-up)
  • AI-powered decision-making (e.g., classify support tickets, generate personalized emails)
  • Data governance (e.g., audit trails, versioning, rollback)

We're not great at:

  • Simple one-off tasks (use Zapier for "new email → add to spreadsheet")
  • Social media scheduling (use Buffer/Hootsuite)
  • Transactional emails (use SendGrid/Postmark directly)

Our clients typically use WRIO for core business processes (onboarding, sales workflows, compliance reports) and keep niche tools for edge cases. We integrate with 50+ services via API, so you can stitch them together into a unified command center.

What happens if Gemini (Google AI) goes down or changes its API?

This is a great question—and exactly why we built provider abstraction. In WRIO, AI is a swappable node:

  • Default: AI_NODE_GEMINI_2_0
  • Fallback: AI_NODE_OPENAI_GPT4 or AI_NODE_ANTHROPIC_CLAUDE
  • Self-hosted: AI_NODE_LLAMA_3_LOCAL

If Gemini has an outage, workflows auto-retry with exponential backoff (3 retries over 5 minutes). If it's a breaking API change, we release a new node version (e.g., AI_NODE_GEMINI_3_0) and migrate workflows gradually. Your old workflows keep running on the old API until you're ready to upgrade.

We learned this the hard way: in December 2025, Google deprecated gemini-1.5-flash with 2 weeks' notice. We had to emergency-migrate 47 workflows. Now we version everything.

How do I get started with WRIO?

Fastest path:

  1. Sign up: https://auth.wr.io/sign_up (GitHub/Google OAuth, 30 seconds)
  2. Try Forge Wizard: https://forge.wr.io/@wrio/kb/demo (upload a PDF, watch AI extract knowledge)
  3. Clone a template: Go to BizCom (https://bizcom.wr.io/wrio/workflows), pick "Lead Enrichment" or "Email Outreach," click "Use Template"
  4. Run your first workflow: Follow the wizard, see real-time logs

For developers:

  1. Read the docs: https://wr.io/wrio/docs (architecture, API reference, JSON-LD schemas)
  2. Clone the repo: git clone https://github.com/webrunes/wrio (if open-sourced) or request beta access
  3. Deploy to Cloudflare: We provide a deploy.sh script that sets up Workers, D1, R2, and Tunnel in 5 minutes

Need help? Email alexey@wr.io or DM me on X/Twitter.