Brian2 Atlas vs Harny
A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.
Brian2 Atlas compared with Harny
| Detail | 
Brian2 Atlas | 
Harny |
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| What it does | Distributed neural simulation with MPI for Brian2 models
| Agent harness infrastructure that gives AI agents memory for each user, connected accounts, action limits and an audit record.
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| Stage | Startup
| Not given
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| Founded | 2026
| Not given
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| Based in | GB
| CA
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| Pricing model | Open source
| Freemium
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| Pricing | Not given
| Free: first 500 monthly-active end users per month, free forever. Paid: $0.30 per monthly-active end user above 500, billed monthly.
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| Key features | - Distributed simulation across MPI ranks
- Multi-backend execution (CPU, GPU, Browser, MPI)
- AtlasIR typed intermediate representation
- Native forward and reverse execution for training
- Retains Brian2 modelling interface
- GPU execution on Apple Metal and NVIDIA CUDA
- WebAssembly browser execution
- CPU reference and AOT compilation
| - Timestamped memory ingestion with backdating capability
- Per-user data isolation and privacy scoping
- Ranked memory recall with dated evidence
- Connected accounts integration per user
- Long-running agent jobs with folder-level operations
- Configurable token ceiling per API call
- Enforced action limits on agent operations
- Complete action audit trail with hash chaining
- MCP server integration for Claude and other clients
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| What makes it different | - Distributed execution without sacrificing Brian2's familiar modelling interface
- Open-source with published arXiv paper and reproduction materials
- Explicit, verifiable execution plans via AtlasIR
| - Highest published BEAM benchmark score at 128K tokens: 85.1, compared to competing memory systems
- 98% fewer tokens required than raw tool output, making responses 4× cheaper
- Works with 20+ agent frameworks including LangChain, LangGraph and LlamaIndex
- First 500 monthly-active end users free forever
- Per-person billing model scales with user growth, not API calls
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| Free plan | Not given
| Not given
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| Open source | Not given
| Not given
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| Platforms | Not given
| Not given
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| Public API | Not given
| Not given
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | Not checked yet ▼ −1 (down) since last check | Not checked yet ● no change since last check |
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| Trust Flow (Majestic) | 3 | 0 |
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| Citation Flow (Majestic) | 19 | 0 |
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| Referring domains (Majestic) | 14 | 1 |
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5 details filled in for both companies.
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