Persistent memory API for AI agents
getmem.ai (getmem.ai) earns a Brand Analyzer score of 69 out of 100, placing it in the Developing tier among SaaS brands, Technology brands. Among 12358 SaaS brands analyzed, getmem.ai ranks in the 46th percentile (category average 69, leader 97). The score combines seven dimensions - name quality, digital presence, visual identity, messaging clarity, trust foundation, AI discoverability, and brand authority - into a single objective benchmark. Dimension scores: Name Quality 98/100, Digital Presence 82/100, Visual Identity 97/100, Messaging Clarity 95/100, Trust Foundation 60/100, AI Discoverability 70/100, Brand Authority 18/100.
getmem.ai is a SaaS memory layer for AI agents and applications. It accepts user and assistant messages via two API calls, extracts typed, structured knowledge through a five-stage, LLM-free heuristic pipeline, and stores it in a hybrid graph-and-vector index. The service returns grounded, ranked context in under 300 milliseconds with 95% fewer tokens, while maintaining strict per-user data isolation.
| Brand Name | getmem.ai |
|---|---|
| Domain | getmem.ai |
| Industry | SaaS, Technology |
| Main Competitors | Mem0, Zep, Letta, LangChain, Pinecone |
Moz Domain Authority 3/100 vs category average 28 / leader 99 - limited third-party links, so AI systems rarely encounter mentions of the brand.
No Wikipedia presence was found - a major gap, since Wikipedia is among the most heavily weighted sources in AI training data.
The homepage meta description reads "Two API calls. Send user and assistant messages. getmem extracts typed knowledge, stores it in a hybrid graph+vector index, and returns grounded context in under 300ms - isolated p…" (Meta description: 34 words. OG description present and descriptive) - this is the summary AI engines are most likely to quote.
Structured data on the homepage: og:title, og:description, og:image, og:type, Twitter cards, canonical. Adding Organization and FAQ schema would further help AI crawlers parse the brand's identity.
AI-crawler access: robots.txt mentions GPTBot, ClaudeBot, PerplexityBot - all allowed - robots.txt controls whether engines like GPTBot and ClaudeBot can read the site at all.
Social footprint: verified profiles on GitHub, Facebook, Instagram, YouTube; no detected presence on X (Twitter), LinkedIn - consistent profiles reinforce the brand's identity across the web.
0 Reddit mentions - community discussion signals real-world reputation to AI models.
getmem.ai scores 17/100 for AI visibility - how well ChatGPT, Claude, Perplexity and Google AI Overviews can discover, identify and cite the brand.
getmem.ai has a weak AI-visibility profile at 17/100 - a proxy for how readily ChatGPT, Perplexity and Google's AI Overviews can recognise and cite it. Its strongest area is recommendation likelihood (48/100) and its weakest is visibility (0/100). It benefits from open access for AI crawlers (GPTBot, ClaudeBot, etc.). The main gaps holding it back: no clear Wikipedia entity to anchor it in LLM training data, no strong Wikidata entry and a low Moz Domain Authority of 3/100.
Common questions people ask in Google, ChatGPT, Claude, Gemini, Perplexity, and other AI search engines.
getmem.ai offers a persistent memory API service for AI agents and applications. The core product accepts conversation messages through two API endpoints, processes them with a five-stage LLM-free heuristic pipeline, stores extracted structured knowledge in a hybrid graph-and-vector index with per-user isolation, and returns ranked, grounded context on demand. The service is delivered as SaaS, targeting developers who need to add stateful, persistent memory to their AI systems.
Sources: getmem.ai official site
getmem.ai's main competitors include Mem0, Zep, Letta, LangChain, Pinecone. These companies compete in the SaaS space for similar customers, offering comparable products or services.
Sources: getmem.ai official site
getmem.ai takes user and assistant messages sent via API, processes them through a five-stage, LLM-free heuristic pipeline, and extracts typed, structured knowledge from those conversations. That knowledge is stored in a hybrid graph-and-vector index on a per-user basis. When queried, it returns ranked, grounded context in under 300 milliseconds using 95% fewer tokens than raw conversation history, enabling AI agents to recall relevant information efficiently.
Sources: getmem.ai official site
getmem.ai is a persistent memory layer service designed for AI agents and applications. It provides a simple two-API-call interface that ingests conversation turns, extracts structured knowledge, and stores it in a hybrid graph-and-vector index. The system is built to give AI agents durable, user-isolated memory that persists across sessions, positioning itself as an infrastructure component for stateful AI development.
Sources: getmem.ai official site
Popular alternatives to getmem.ai include Mem0, Zep, Letta, LangChain, Pinecone. Each is an established option in the SaaS space; the best fit depends on your specific needs, budget, and required features.
Sources: getmem.ai official site
getmem.ai has low AI-search visibility, scoring 17/100 on Brand Analyzer's AI visibility composite (visibility 0, trust 17, recommendation 48). This estimates how likely AI engines like ChatGPT, Claude, Gemini and Perplexity are to know, trust, and recommend the brand.
Sources: getmem.ai official site
getmem.ai and Mem0 are competitors in SaaS. They target overlapping audiences; the right choice depends on your specific needs and priorities.
Sources: getmem.ai official site
getmem.ai is known for its high-speed, low-token memory retrieval for AI agents. Key distinguishing characteristics include sub-300-millisecond response times, a 95% token reduction compared to passing raw conversation history, strict per-user data isolation, and an LLM-free five-stage heuristic extraction process. It is also noted for its minimal integration surface - just two API calls - making it straightforward to add persistent memory to AI applications.
Sources: getmem.ai official site
getmem.ai scores 48/100 on Brand Analyzer's AI recommendation signal, indicating it is less likely to be surfaced when AI assistants like ChatGPT suggest SaaS options. Recommendation depends on crawlability, structured data, and category authority.
Sources: getmem.ai official site
According to the available information, getmem.ai targets developers and companies that are building AI agents and AI-powered applications. Specifically, it is intended for teams that require persistent, user-isolated memory in their systems - for example, those building conversational AI, autonomous agents, or other stateful AI workflows where remembering past interactions across sessions is a core requirement.
Sources: getmem.ai official site
getmem.ai can improve AI discoverability by strengthening structured data (Organization and FAQ schema), maintaining an accurate Wikipedia/Wikidata entity, earning authoritative citations, and keeping content crawlable for AI bots. Brand Analyzer measures these as visibility, trust, and recommendation signals.
Sources: getmem.ai official site
Ranked closest to getmem.ai: Curate (69/100), aglow (69/100), Packup (69/100), Parallel (69/100).
A step up - brands to learn from: ZyG (71/100), Zuant (71/100).
Category leader: Accenture (97/100).