When Do Customers Mention This Competitor?
- "We already use a workflow automation tool, why switch to 361?"
- "Our current automation tool is enough, it connects everything."
- "We have a no-code automation solution, why pay for AI?"
- IT built hundreds of "if-then" scenarios; management says "we have automation".
3 Critical Differences
1. Data Layer: No Entities in Automation Tools — Entity-Native Architecture at 361
- Workflow automation tools: Move data between systems but do not understand what the data is. No concept of "customer", "invoice", "order" — they just copy JSON fields.
- 361: Entity-Native architecture — all business objects of 200+ ready business modules are defined. AI "understands" customers, invoices and orders and works in context. Not moving data — making sense of it.
- Proof: "Show last month's 5 riskiest customers" — you cannot build this query in an automation tool. One sentence in 361.
2. AI: Rule-Based If/Then vs Autonomous Agents + Real State Machine
- Workflow automation tools: Static rules: "if A then B" (simple trigger-action). They break on exceptions; you build a new flow for every scenario.
- 361: AI agents decide autonomously; underneath runs a real state-machine workflow (state/transition/guard/role/condition + live simulator). If an invoice amount falls outside the expected range, it stops, analyzes, checks history and proposes. Instead of writing rules, you give the agent a goal.
- Proof: 17 AI providers (including embedded local361/llama.cpp) + 52 built-in tools — agents use the most suitable model for the context. Plus: every state transition is logged automatically; Process Miner shows bottlenecks from real records — no separate process-mining product (Celonis-style) or event-log ETL needed.
3. Security: Data Leaves vs Guardrails + Local Models
- Workflow automation tools: Your data is processed on third-party servers. Customer info, financial data, personal data flows out. You cannot explain these flows in a KVKK audit.
- 361: 4 guardrail detectors (PII, hallucination, prompt-injection, content) + GuardrailPipeline; local model support (embedded local361/llama.cpp, Ollama — data never leaves), AES-256 encryption, role-based access, immutable audit trail.
- Proof: KVKK/GDPR compliant, full audit log, every AI action on record.
Objection Handling
| Objection | Response |
|---|---|
| "Hundreds of flows already run" | Keep the useful ones as integrations. Move the decision-heavy ones to 361 agents — that is where the real gain is. |
| "Zapier is cheap" | For simple triggers, yes. For governed, entity-aware, auditable enterprise processes, the comparison ends there. |
| "Our data is not sensitive" | Customer and finance data is sensitive by law. Guardrails + local models remove the discussion entirely. |
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