Phidata / Agno
Phidata rebranded to Agno in 2024. OSS Python framework for building multi-agent systems with memory, knowledge, tools, reasoning. Lightweight alternative to LangChain. ~25k+ stars combined Phidata + Agno repos. Mozilla Ventures + others backed. Distinct from Mem0 / Zep — Agno is a full agent framework with first-party memory + knowledge + reasoning + tools.
At a glance
- Type
- OSS multi-agent framework (rebranded from Phidata to Agno 2024)
- Tier
- T2
- Created
- 2023 (Phidata initial); 2024 (Agno rebrand)
- Latest release
- not applicable — orchestration platform, not memory product
- License
- MPL-2.0 (Agno OSS)
- Pricing
- OSS (free); future paid cloud tier
- Funding
- Pre-seed / seed disclosed (~$5M+); Mozilla Ventures + Y Combinator (W22) participation
Taxonomy
- storage
- none-trivial
- retrieval
- none
- persistence
- session-only
- update
- agent-controlled
- unit
- turn
- governance
- opaque
- conflict
- out-of-scope
When to use
Optimised for: lightweight Python multi-agent systems; alternative to LangChain bloat
Anti-fit: not applicable — orchestration platform, not memory product
Pros & cons
Pros
Lightweight Python framework; first-party memory + knowledge + reasoning + tools (no LangChain dependency); 25k+ stars combined; clean docs.
Cons
Smaller ecosystem than LangChain / LlamaIndex; rebrand from Phidata creates discovery friction; pre-product commercial revenue.
Claims & capabilities
OSS Python framework (MPL-2.0); rebranded Phidata → Agno 2024; 25k+ stars (Phidata + Agno cumulative); pre-seed + seed funded (Mozilla Ventures + others)
Technical surface
- API surface
- not applicable — orchestration platform, not memory product
- Backend storage
- not applicable — orchestration platform, not memory product
- Deployment
- not applicable — orchestration platform, not memory product
- Embedding model
- not applicable — not a memory product
- Multi-tenancy
- not applicable — orchestration platform, not memory product
- MCP
- native (first-party)
- A2A
- not applicable — orchestration platform, not memory product
- OpenTelemetry
- not applicable — orchestration platform, not memory product
Compare Phidata / Agno with…
Similar systems
Other multi-agent orchestration platforms in the catalog, ranked by inbound references.
- Adept ACT T3
Founded 2022 by ex-OpenAI / Google researchers (David Luan, Kelsey Schroeder). Built ACT-1 / ACT-2 multimodal action transformers for computer-use. **Acquired by Amazon June-2024 (acqui-hire)** — co-founders + key team joined Amazon AGI; Adept the company continues with Zach Brock as remaining executive. Important historical entry — ACT models inspired Anthropic Computer Use + OpenAI Operator.
- Burr (DAGWorks) T2
Burr is a state-machine framework for LLM agents from DAGWorks (commercial company behind Hamilton dataflow framework, $4M seed). State-machine abstraction instead of DAG / ReAct — more debuggable for production. Targets the same niche as LangGraph but with state-machine semantics rather than DAG. BSD-3 license. Founded 2023 by ex-Stitch Fix / Two Sigma / Lyft engineers.
- CrewAI Enterprise T2
Commercial Enterprise tier of the CrewAI OSS multi-agent framework. Adds managed cloud runtime, RBAC, audit logging, SLA support, on-prem option. OSS CrewAI is in the Framework-embedded memory section already; this row covers the commercial cloud platform separately. $18M Series A Oct-2024 (Insight Partners). 30k+ companies have deployed CrewAI agents in prod (vendor-stated).
- Imbue (formerly Generally Intelligent) T3
Founded 2017 as Generally Intelligent; rebranded Imbue 2023. Building foundation models for reasoning agents that write/edit code. Founders Kanjun Qiu + Josh Albrecht. $200M Series B 2023 ($1B valuation, Astera + Nvidia + Notion's Akshay Kothari). Trained 70B model for reasoning. Most public output is research blog + 'Carbon' OSS coding agent. Pulled back commercial roadmap post-2024.
- InstructLab (Red Hat / IBM) T2
Red Hat / IBM-stewarded open-source framework for community-driven LLM alignment + fine-tuning. Method paper 'LAB: Large-Scale Alignment for Chatbots' (Sudalairaj et al, IBM Research 2024). Built on the Granite model family (IBM's open-weights). Apache 2.0. Used in IBM watsonx + Red Hat OpenShift AI for fine-tuning workflows. Not strictly a multi-agent framework — included as 'orchestration platform' because of its role as a substrate for building domain-specific fine-tuned agent models.
- Lindy T2
Lindy is a no-code multi-agent automation platform from Florent Crivello (ex-Teleport, ex-Twitter). Targets consumer / SMB segment with email triage, meeting scheduling, CRM-update agents. $50M Series A Oct-2024 led by Andreessen Horowitz + Sequoia. Distinct from Zapier / n8n traditional automation by putting LLMs at the core of every workflow node.
Related systems
References (4)
- Anthropic Claude (foundation models) depends on at runtime — adjacent-infrastructure cell: HuggingFace Transformers; OpenAI / Anthropic / Gemini SDKs; YC W22 alumni network
- Google Gemini 3 family depends on at runtime — adjacent-infrastructure cell: HuggingFace Transformers; OpenAI / Anthropic / Gemini SDKs; YC W22 alumni network
- LangChain (framework) competes with — soning. Lightweight alternative to LangChain. ~25k+ stars combined Phidata + Agno repos. Mozilla Venture
- OpenAI GPT family (GPT-5 / GPT-4o / o3 / o4) depends on at runtime — adjacent-infrastructure cell: HuggingFace Transformers; OpenAI / Anthropic / Gemini SDKs; YC W22 alumni network