Fastino

Name: Fastino
Brand: Fastino

AI Native

Building the next generation of small language models.

Est 2024|Valuation $128M|Raised $24.6M

LinkedIn 14K|Web traffic 16K|FTEs 29|HQ Palo Alto, us

01Competitive Landscape

Fastino operates across two adjacent spaces: agent memory/personalization and information extraction. The following practical comparison focuses on the agent memory / personalization category where buying decisions are common.

Narrative analysis

Fastino vs Mem0 - Mem0 has clear publicly documented pricing tiers and a simple memories model. Fastino differentiates by combining an extraction model (GLiNER2) with a personalization API; buyers whose primary requirement is memory abstraction may find Mem0 easier to evaluate and procure. Fastino vs Zep - Zep emphasizes context engineering and temporal/graph-based memory; Fastino emphasizes task-optimized extraction plus personalization. Public materials for Zep include more explicit enterprise security claims in some plans; Fastino’s public compliance artifacts were not verifiable in this research pass. Fastino vs "roll your own" (LangChain Memory + DB/vector store) - Building a custom memory and extraction stack can be lower cost initially and more customizable, but places the burden of data lifecycle, scaling, monitoring, and operations on the buyer. Fastino aims to consolidate these capabilities into a single API; buyers should validate whether integration reduces or shifts operational complexity.

	Fastino (Personalization API + GLiNER2)	Mem0	Zep
Starting Price	Metered token-based pricing for extraction API; personalization offered via tiered plans (metered/subscription).	Free tier available; entry-level paid tier for hobby/small teams; higher-tier plans for teams.	Entry-level subscription available; higher tiers for business/enterprise usage.
Best For	Teams requiring CPU-capable extraction and a persistent personalization layer for agents.	Teams seeking a managed memory product with clear tiers and a simple memory abstraction.	Teams focused on temporal/graph memory and context engineering with enterprise deployment options.
Key Strength	Open-source GLiNER option; emphasis on low-latency extraction; privacy lifecycle controls described in public materials.	Clear pricing and straightforward buying motion; managed memories abstraction.	Explicit positioning around temporal knowledge graphs and enterprise options; documented enterprise features on some plans.
Key Weakness	Limited third-party reviews in public record; compliance and enterprise artifacts require verification; personalization pricing not clearly published.	May not cover graph/temporal capabilities required by complex agent workflows.	Pricing and credit accounting can be complex; learning curve for message/episode accounting.

01Competitive Landscape

Narrative analysis

Fastino vs Mem0

Mem0 has clear publicly documented pricing tiers and a simple memories model. Fastino differentiates by combining an extraction model (GLiNER2) with a personalization API; buyers whose primary requirement is memory abstraction may find Mem0 easier to evaluate and procure.

Fastino vs Zep

Zep emphasizes context engineering and temporal/graph-based memory; Fastino emphasizes task-optimized extraction plus personalization. Public materials for Zep include more explicit enterprise security claims in some plans; Fastino’s public compliance artifacts were not verifiable in this research pass.

Fastino vs "roll your own" (LangChain Memory + DB/vector store)

Building a custom memory and extraction stack can be lower cost initially and more customizable, but places the burden of data lifecycle, scaling, monitoring, and operations on the buyer. Fastino aims to consolidate these capabilities into a single API; buyers should validate whether integration reduces or shifts operational complexity.

	Fastino (Personalization API + GLiNER2)	Mem0	Zep
Starting Price	Metered token-based pricing for extraction API; personalization offered via tiered plans (metered/subscription).	Free tier available; entry-level paid tier for hobby/small teams; higher-tier plans for teams.	Entry-level subscription available; higher tiers for business/enterprise usage.
Best For	Teams requiring CPU-capable extraction and a persistent personalization layer for agents.	Teams seeking a managed memory product with clear tiers and a simple memory abstraction.	Teams focused on temporal/graph memory and context engineering with enterprise deployment options.
Key Strength	Open-source GLiNER option; emphasis on low-latency extraction; privacy lifecycle controls described in public materials.	Clear pricing and straightforward buying motion; managed memories abstraction.	Explicit positioning around temporal knowledge graphs and enterprise options; documented enterprise features on some plans.
Key Weakness	Limited third-party reviews in public record; compliance and enterprise artifacts require verification; personalization pricing not clearly published.	May not cover graph/temporal capabilities required by complex agent workflows.	Pricing and credit accounting can be complex; learning curve for message/episode accounting.

Fastino

01Competitive Landscape

Narrative analysis

02Market Map

01Competitive Landscape

Narrative analysis

02Market Map