Cache ≠ memory.
And nobody verifies.
Researched October 2026 from docs, pricing pages, and benchmarks — not marketing.
| Memflex | Jev (TypeSafe) | Mem0 | Portkey | GPTCache | |
|---|---|---|---|---|---|
| Answers repeats, zero LLM | ✅ core | ✅ (trained) | ❌ facts only | ✅ cached | ✅ cached |
| Calibrated confidence | ✅ per-reflex | ✅ RLCD | partial | ❌ | ❌ |
| Self-correction loop | ✅ verify + 👎 | ❌ | ❌ | ❌ | ❌ |
| Cost on repeats | ₹0 | $42/B tokens | $19+/mo + tokens | per-token + Enterprise | free, self-run |
| Multilingual-first | ✅ 19 langs tested | EN-first | ❌ | ❌ | ❌ |
| Self-host, 1 command | ✅ SQLite / Postgres | ❌ hosted | partial | partial / Enterprise | ✅ + Milvus |
| Unseen generalization | ❌ → LLM | ✅ trained | ✅ LLM | ✅ LLM | ✅ LLM |
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Don't take our word for it — measured.
30 questions customers actually ask — refunds, cancellations, delivery tracking — in English, German, Spanish and French, each asked 3 different ways. Result: 22 answered from memory at ₹0.
At 1 lakh asks a month with 70% repeats, that's roughly 70,000 free answers — about ₹21,000–35,000/month saved, plus instant replies instead of multi-second waits.
Honest limits: mock-backend latency flatters absolutes — the real delta is memory-path ms vs your LLM's seconds. Hit-rate follows your repeat rate; unique-every-time workloads gain nothing.
The moat is a combination, not a trick: zero-call repeats + verified memory + multilingual + free self-host. Where giants overlap, Memflex plugs in beside them.