Jev vs Vilix AI: The Decision Layer and the Memory Layer
Jev and Vilix AI are not competitors. One makes fast judgments, the other remembers them. When you need each, and how they fit together.
Jev vs Vilix AI: The Decision Layer and the Memory Layer
Direct answer: Jev and Vilix AI are not competitors. Jev makes fast, cheap, calibrated judgments. Vilix AI remembers context, decisions, and lessons across every AI tool you use. If you run scheduled agents, you probably want both: Jev to decide, Vilix AI to remember.
Side by side
| Jev (TypeSafe AI) | Vilix AI | |
|---|---|---|
| Job | Typed decisions: choice, score, yes-or-no probability | Shared memory and work state across AI tools |
| Output | A pick, a score, or a probability, each with confidence | Context, rules, tasks, skills, full conversation history |
| Speed | 70 to 500 ms per call | Memory retrieval in about a second |
| Price | $0.042 per million input tokens, output free | Free plan; paid plans from $10/mo |
| Remembers between calls | No, every call is stateless | Yes, that is the whole product |
| Generates text | No | No, it stores and retrieves; your AI tools do the talking |
When you need Jev
You need Jev when your agent makes millions of tiny judgments: routing tickets, moderating content, reranking search results, enforcing guardrails, verifying another model's output. Anywhere you currently make an LLM write JSON and pray it parses, Jev does it faster, cheaper, and with a real confidence number. The independent benchmark found it 6 to 18 times faster than LLMs on the server and 84 to 150 times cheaper than the most expensive models, with the best score of six models on content moderation.
When you need Vilix AI
You need Vilix AI whenever two runs, two tools, or two days need the same context. Scheduled agents that wake up blank every invocation. Handoffs between Claude and Codex mid-project. Rules you set once and want enforced everywhere. Skills your agents reuse instead of relearning. It connects over MCP to every major AI tool, stores full exchanges plus derived memories, projects, tasks, and reusable skills, and the latest write wins when two tools disagree, so you only ever correct something in one place. Your data stays portable: export everything or delete it anytime.
How they fit together
This is the combination most operators miss. A Jev judgment is brilliant and instantly forgotten. A Vilix AI memory without fresh judgments goes stale. Together they cover the full loop:
- The agent gathers state.
- Jev judges it in one parallel pass (team, urgency, priority, each with confidence).
- The judgment is saved to Vilix AI over MCP.
- Every future run, in every tool, reads the stored judgment instead of re-judging.
We published the full working pattern as a cookbook: Vilix AI x Jev Cookbook. It includes the exact MCP session handshake and a ticket-triage example you can adapt.
The honest verdict
Jev is the strongest option we have seen for the decision layer: real calibration numbers, real speed, real price advantage, and an honest "we can still pick the wrong valid option" failure mode instead of hallucinated prose. Vilix AI is the memory layer that makes those decisions stick across tools and time.
The expensive stack is the one that makes brilliant decisions and forgets them by morning. Buy the fast gut and the long memory, and stop paying for the same judgment twice.
Free forever, no credit card. Paid plans start at $10/mo, with a 7-day Pro trial that needs no credit card.