Clearbit
Lusha
Apollo.io
DiscoverOrg
Hunter.io
ZoomInfo
UpLead
Lead411
Tempreon
ChainMemory
Memori
Agentmemory
OpenMemory MCP
TheSecondBrain.dev
cognee
VATES.jp
Tempreon is a personal memory layer for your AI tools, connected over MCP. Your knowledge, preferences, and decisions travel across Claude, ChatGPT, Cursor, and any MCP-capable client โ captured once, available everywhere. It learns how you actually work instead of just storing what you said.
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Tempreon's answer:
Tempreon started with a simple observation: AI models keep changing, but the thing that makes them useful to you โ your context, your preferences, your judgment โ gets rebuilt from scratch inside every tool, and lost every time you move.
We built the layer that fixes that: person-owned memory served over the open Model Context Protocol, so it works across assistants instead of belonging to one. Along the way we open-sourced the pieces that are useful to everyone regardless of whether they use Tempreon โ like memhaul, our MIT-licensed CLI for turning ChatGPT and Claude data exports into files you own.
The through-line is custody: the model is temporary, your memory shouldn't be.
Tempreon's answer:
Most alternatives in this space are memory infrastructure for developers building their own AI apps. If you're the person using several AI tools every day, that's not your problem โ your problem is re-explaining yourself to each of them and losing everything when you switch.
The choice is really about who the memory is for. Ours is for you.
Tempreon's answer:
Tempreon is built for the person, not the app. Most memory products are developer APIs for adding memory to a single product; Tempreon is a memory layer you own that travels with you across every AI tool you use โ Claude, ChatGPT, Cursor, anything MCP-capable.
Tempreon's answer:
Individuals who live in AI tools all day: operators, consultants, founders, sales professionals, and knowledge workers who use more than one assistant and are tired of being a stranger to each of them.
If you've ever pasted the same context into Claude and ChatGPT in the same week โ you're the audience.
Tempreon's answer:
The protocol choice is the product decision: build on the open standard, and your memory works everywhere the standard does.
Based on our record, Clearbit seems to be more popular. It has been mentiond 18 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Some display names need a lookup table, not fuzzy strings. Pairs like Investing.com / Fusion Media Limited or Lyrie.ai / OTT Cybersecurity Inc. Share almost no tokens, so WRatio stays low and that's correct behavior. For irreconcilable aliases like that you still want GLEIF, Clearbit, or simply a maintained slug โ legal_name map. Fuzzy matching handles stylistic drift on the same name; it canโt handle unrelated... - Source: dev.to / 2 months ago
Personal email domains destroy this. Clearbit's Enrichment API returns a null company when it hits gmail.com. Apollo routes personal domains straight to a consumer bucket and skips B2B fields entirely. Even PDL's /person/enrich endpoint โ the most permissive of the major providers โ gives you around 32% hit rate on Gmail addresses versus 74% on corporate domains. I measured this across 6,200 signups for a... - Source: dev.to / 3 months ago
A few things worth flagging: PDL beats Clearbit's historical rates for US and Western European companies, but drops to ~52% match rate for Japan and South Korea specifically. Apollo underperforms on raw company matching but returns significantly more contacts per domain in Prospector-style queries than Clearbit's Prospector ever did โ the tradeoff is more stale titles in the result set. Hunter.io is fast and cheap... - Source: dev.to / 3 months ago
Match rate of 38% in my test, but the data quality on what it does match is solid: title, seniority, industry, company size all returned cleanly. If you're already in HubSpot and enriching form fills in-place, Clearbit/Breeze is probably your lowest-friction option even at lower match rates. If you're not in HubSpot, there's no reason to choose it over PDL or Prospeo. - Source: dev.to / 3 months ago
One thing comparison guides consistently get wrong: Clay is not an enrichment API. It's a waterfall orchestration tool that calls People Data Labs, Apollo, Clearbit, and others in sequence for you. It's useful, but it adds 2โ8 seconds of latency per row in my runs and costs more per match than going direct. For a CRM webhook flow where you need sub-second enrichment calls, Clay is the wrong layer to hit first. - Source: dev.to / 3 months ago
Lusha - Search less. Sell more.
ChainMemory - Portable, verifiable memory for AI agents โ works across ChatGPT, Claude, Gemini and any MCP client
Apollo.io - Apolloโs predictive prospecting, sales engagement, and actionable analytics help the teams to reach its full revenue potential.
Memori - Persistent memory from agent trace, not just conversation
DiscoverOrg - DiscoverOrg is an IT sales intelligence platform providing technology marketers access to data, IT org charts, and real time projects.
Agentmemory - Persistent memory for Claude Code, Codex & coding agents