Atomic Strata builds high-performance, configurable context for AI applications, agents, and enterprise workflows.
Santa Monica, CA
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- Followers 2,117
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Let your system run autonomously.
Give your agents memory they can use across sessions, and your team a way to see what was stored, retrieved, corrected, and why.
Configurable memory for AI agents, now in Public Beta.
memory.atomicstrata.ai/?utm_…
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We achieved 2.1k GitHub stars for LLM Wiki Compiler!
This milestone belongs to everyone who has explored the project, shared feedback and contributed along the way. We're grateful to have an awesome dev community building with us!
Disclaimer: no LLMs were harmed in the making of this repo
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Check out the repo here 👇
github.com/atomicstrata/llm-…
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Keep your organization's operating knowledge current.
When someone corrects a process, the agent updates the relevant guidance and retrieves the latest version when another teammate needs to act.
Turn every correction into better operations.
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Opus 5.5 release looks seriously impressive for agentic work.
Matching Fable 5.1 on most tasks while costing 40% less to run than Opus 5. This model can handle multi-hour coding tasks, build playable games from a single prompt, generate procedural animations through code, and port complex systems such as HAProxy from C to Rust.
@AnthropicAI raises the bar for what agents can accomplish!
Introducing Claude Opus 5.5, the first model in our new Claude 5.5 family.
It performs at the level of Claude Fable 5.1 for most tasks, and costs 40% less to run than Opus 5.
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Scale your AI products across more deployments.
Developers should be able to support private context without rebuilding the product for every environment. One architecture can serve multiple deployments while keeping each workspace isolated and reliable.
Increase your profits without multiplying technical complexity.
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Claude support in Hermes Agent is a strong step toward a provider-flexible agent stack.
Hermes users should be able to bring their memory wherever they run. Give your agents configurable memory that stays portable across models, tools, and sessions.
memory.atomicstrata.ai/?utm_…
Welcome back to Hermes Agent, Claude
New official plugin that uses Claude SDK without the tradeoffs to enable Claude Code subscriptions to work in Hermes Agent again!
Check it out and install it here: hermes-agent.nousresearch.co…
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What does enterprise AI need before it can be trusted with real work?
Our founder @jbruce shares what Atomic Strata is building: governed AI context memory that enterprises can configure, inspect, and correct.
Watch our showcase with Imagination in Action @imaginationxyz @johnkwerner
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Organizations ships SaaS way faster without burning runway on context.
Your coding agent now knows every codebase update, so it avoids repeatedly building the same context.
Keep your SaaS worry-free and generate revenue back to you without a hassle.
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We help big organizations close deals faster without paying for a CRM.
Work with an agent that remembers every lead touchpoint so you close deals faster without paying for a CRM that nobody updates
Turn every follow-up into revenue.
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Run 10 client accounts without the 10x overhead from session spending.
These agents keeps every account’s memory from decay, helping your team deliver consistent output across accounts at a fraction of the usual overhead.
Put your next 10 accounts on one agent.
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Make your agent memory portable so you can switch anytime.
Atomic Memory Cloud works through HTTP, TypeScript, Python, CLI, MCP, and framework adapters, so teams can start hosted while keeping a self-host path open.
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Find out why your agents hallucinate.
Developers need the full memory receipt in one place before they can fix production behavior.
Debugging memory is easy with Atomic Memory Cloud. memory.atomicstrata.ai/?utm_…
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An enterprise agent should remember where the last conversation ended. Continuity makes every interaction more dependable.
Power your agents with Atomic Memory Cloud.
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Atomic Strata retweeted
I'm speaking about governed context memory for Enterprise AI at the Stanford HAI and MIT Silicon Valley AI Summit hosted at Google DeepMind today.
AI context needs to be configurable, inspectable, correctable and auditable to meet enterprise needs. Atomic Strata is building this context stack today.
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"The relationship between an idea and the effort required to realize it has crossed a threshold with AI."
Our CTO experienced that shift when GPT-6-astra rebuilt a musical instrument he first wrote in assembly language in 1989. His story shows how AI can make more ambitious ideas buildable.
Read the full story below.
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Work with an AI knowledge compiler that understands your whole project.
LLM-Wiki Compiler v1.3.0 adds recursive source discovery, literal path exclusions, project-specific compile instructions, and four viewer themes for your wiki.
Check the full summary → github.com/atomicstrata/llm-…
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We just made your AI wiki compiler more powerful.
LLM-Wiki Compiler v1.2.0 turns source materials into durable knowledge that teams can inspect, version, and carry across tools with OKF export/import.
Try it out now → github.com/atomicstrata/llm-…
We shipped LLM-Wiki Compiler v1.2.0.
The product direction is simple.
Turn source material into durable knowledge that can be reviewed, moved, and reused.
The new OKF export/import path matters because useful knowledge should not be trapped in one tool's folder shape.
Teams will want compiled knowledge they can inspect, version, and carry forward.
github.com/atomicstrata/llm-…
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Release notes for v1.2.0:
1. Explore documents more easily with categories, linked records, source previews, provenance, responsive navigation, and fitted graphs.
2. Connect more providers and customize reasoning models, embeddings, and SDK settings.
3. Add source lists, system policies, and page-level provenance to your knowledge base.
4. Recover shared pages after source removal, with improved citations and wikilink repair.
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