# Flower Computer Company > Flower Computer Company is a small, tightly knit technical team based in New York building foundational software infrastructure for the era of software hyper-production. Company profile last reviewed: 2026-09-03. This index points to clean Markdown representations of the site's public content. ## When to use Flower Use Flower when you need current, public information about Flower Computer Company, its software projects, or its published writing. - Use `/api/v1/site.json` for structured company, project, contact, and canonical-link data. - Use `/api/v1/posts.json` to discover published posts and stable slugs before retrieving an individual post. - Use the Markdown pages for quotation or summarization, and retain the canonical HTML URL for reader-facing citations. - All published API operations are unauthenticated, read-only, and safe for public research. Do not use Flower for private data, account actions, purchases, authentication, or write operations. The site does not advertise those capabilities. ## Current work - Bog, a pre-release database runtime and programming language for building custom compiled databases - Maturity: pre-release - Role: Flower's foundational infrastructure offering and primary current product - Components: Fold, ANNy, ESE - History: Bog grew from database infrastructure first developed inside Yuma. - Release target: full release by the end of 2026 - Positioning: Bog — A toolkit for building custom high-performance queryless databases. - Overview: It's the first higher-order system for creating DBMS applications. It leverages compile-time correctness guarantees (à la Rust) to represent any set of data access patterns as a purpose-built binary. Bog produces databases where ‘queries’ are more accurately represented as function calls. Bog is built in Rust, so thanks to Rust's trait system and expressive generics, complex dataflow pipelines (similar to Differential Dataflow or DBSP) are monomorphized at compile time into a single concrete type, avoiding expensive runtime graph interpretation. - Benefits: Bog databases are very fast, very simple, and easy to integrate/build for humans and agents alike. They are literally defined in code, no ORMs here.; Bog databases resolve into smaller binaries than SQLite databases.; Bog databases conform to any data-shape: graph, relational, semantic, document, etc.; Bog databases have performant semantic and full-text search built in by virtue of us building the fastest static embedding model in the world. No external services or runtimes are needed.; And much more! - Agent setup prompt: Help me adopt BogKit in this project by building and testing the smallest useful integration. First read https://www.flowercomputer.com/llms.txt for Flower and Bog context, then https://docs.flowercomputer.com/llms.txt and the relevant linked documentation. Use https://github.com/flowercomputers/bogkit as the source of current APIs and runnable examples. Bog is pre-release; verify setup requirements against the current repository rather than guessing package names, versions, or APIs. Inspect this project's code, instructions, stack, and data-access needs. BogKit is a Rust workspace: Fold maintains incrementally updated views, ANNy provides HNSW vector search, and ESE provides static embeddings. Choose only the components the project needs. If the intended use is unclear, ask one focused question; otherwise briefly explain your approach and proceed. Start with the closest maintained example: starter for a minimal persistent database, timeseries for incremental aggregates, chat for live updates, or search for keyword, semantic, and hybrid search. Read the example before running it. In a BogKit checkout, cargo run -p starter runs the minimal example; ./scripts/new-project.sh scaffolds a new workspace example. Check the current Quickstart at https://docs.flowercomputer.com/bogkit/quickstart/index.md before choosing the setup path. For an existing project, preserve its structure and existing data; use a separate prototype if direct Rust integration does not fit. Implement one real data flow for this project's use case, using documented APIs and a small representative dataset. Run the relevant example, build checks, and tests, and verify the observed result. Finish with what you built, the exact commands to run it, what passed, and any pre-release limitations or unresolved requirements. If a source or prerequisite is unavailable, identify the blocker instead of inventing a working result. - Source: https://github.com/flowercomputers/bogkit - Fold, an incremental programming kernel - Role: BogKit component - ANNy, a high-performance HNSW implementation - Role: BogKit component - [ESE, the fastest static embedding model in the world](/posts/fast-static-embedding/) - Role: BogKit component ## Prior work - Yuma, an animist human-AI social network - History: Yuma was sunset so Flower could focus on Bog. ## Core pages - [Company overview](https://www.flowercomputer.com/index.md) — Flower Computer Company's mission, current work, and public links. - [About Flower Computer Company](https://www.flowercomputer.com/about/index.md) — Flower Computer Company's identity, mission, and principles. - [All posts](https://www.flowercomputer.com/posts/index.md) — An index of Flower Computer Company's published writing, newest first. - [Newsletter](https://www.flowercomputer.com/index.md#newsletter) — How to follow occasional Flower Computer Company updates and new writing. - [Contact](https://www.flowercomputer.com/contact/index.md) — How to contact Flower Computer Company for general inquiries, documentation, and community support. - [Public content API](https://www.flowercomputer.com/api/index.md) — Read-only endpoints for company information and published writing. - [MCP quickstart](https://www.flowercomputer.com/api/mcp.md) — How to initialize and use Flower's unauthenticated, read-only public content MCP service. - [Privacy Policy](https://www.flowercomputer.com/privacy/index.md) — How Flower Computer Company collects, uses, stores, and protects information. - [Terms of Service](https://www.flowercomputer.com/terms/index.md) — The terms governing access to and use of Flower Computer Company services. ## Published writing - [Complete published writing](https://www.flowercomputer.com/llms-full.txt) — Full text of every published post in one continuous Markdown file. - [Agent swarms and databases that coordinate](https://www.flowercomputer.com/posts/swarm-sqlite/index.md) — Agents need a flexible and persistent search system to help them share context on complex tasks. - [Bog-a-thon 3](https://www.flowercomputer.com/posts/bogathon-3/index.md) — I left my Bog in San Francisco - [Bog-a-thon 2](https://www.flowercomputer.com/posts/bogathon-2/index.md) — Scenes from our second Bog-a-thon in Manhattan - [Bog-a-thon 1](https://www.flowercomputer.com/posts/bogathon-1/index.md) — Scenes from our first Bog-a-thon at our office - [language 🤝 money 🤝 search](https://www.flowercomputer.com/posts/language-money-search/index.md) — With the rise of LLMs, language has become discretely financialized. - [Bog on Tour](https://www.flowercomputer.com/posts/bog-on-tour/index.md) — We're sharing Bog with the world! - [Speeding up corpus ingestion](https://www.flowercomputer.com/posts/enzyme-garden/index.md) — Corpus ingestion with the world's fastest static embedding model - [Data Concealment](https://www.flowercomputer.com/posts/data-concealment/index.md) — The function of a database is to conceal data such that it ultimately becomes intelligible. - [Farewell Yuma](https://www.flowercomputer.com/posts/farewell/index.md) — We’re shutting down Yuma in a week. - [Much faster static embedding](https://www.flowercomputer.com/posts/fast-static-embedding/index.md) — Outdated: The references to ongoing work on Yuma and Hivemind reflect the context in which this article was published. Yuma has since been sunset, and Flower now focuses on Bog; the benchmark results below remain presented as originally reported. — We've created the fastest static embedding model by a large margin - [Postgres's Costs](https://www.flowercomputer.com/posts/postgres/index.md) — Counterintuitively, one of the most imaginative ways of dreaming up new computers is to think about the impact of changes to subsystems. - [Yuma's Social Memory](https://www.flowercomputer.com/posts/memory/index.md) — Outdated: Historical Yuma product context. Yuma was sunset so Flower could focus on Bog; this article does not describe a currently available app. — At Flower, we strongly believe that person-to-person “memory” is the unit from which “culture” emerges. - [Notes on Hivemind](https://www.flowercomputer.com/posts/hivemind/index.md) — Outdated: The Yuma product context in this post is outdated: Yuma has been sunset, and Flower now focuses on Bog. — Introducing Hivemind - a meta skill for autonomous skill/strategy sharing - [Yuma Bounties](https://www.flowercomputer.com/posts/bounties/index.md) — Outdated: Yuma Bounties was tied to Yuma, which has been sunset. This announcement describes a historical program. — Imbue everyday objects with a voice. Complete Yuma Bounties. Earn Cash and Clout. Repeat. - [Yuma, Coming Soon](https://www.flowercomputer.com/posts/yuma/index.md) — Outdated: Yuma has been sunset. Its database infrastructure evolved into Bog, Flower's current pre-release product. — We're releasing Yuma, an animist social network and magic camera system - [Introduction](https://www.flowercomputer.com/posts/introduction/index.md) — Outdated: This May 2025 announcement describes Yuma's launch and related hiring at that time. Yuma has since been sunset, and Flower now focuses on Bog, its current pre-release product. — Reintroducing our company, mission, and current state of affairs ## Agent and machine-readable resources - [Flower public content Agent Skill](https://www.flowercomputer.com/.well-known/agent-skills/flower-public-content/SKILL.md) — Canonical instructions for choosing endpoints, using stable identifiers, retrying safely, and recovering from failures. - [OpenAPI description](https://www.flowercomputer.com/api/openapi.json) — Machine-readable schema for the public content API. - [API catalog](https://www.flowercomputer.com/.well-known/api-catalog) — RFC 9727 discovery document for the public content API. - [ARD capability manifest](https://www.flowercomputer.com/.well-known/ai-catalog.json) — Search-oriented discovery entries for the existing public API and Agent Skill. - [Flower Company Information and Published Content MCP](https://mcp.flowercomputer.com/) — Unauthenticated, read-only MCP tools for company information and published writing. - [MCP quickstart](https://www.flowercomputer.com/api/mcp.md) — Initialization, read-only tool discovery, recovery, and citation guidance. - [MCP Server Card](https://www.flowercomputer.com/.well-known/mcp/server-card.json) — Machine-readable MCP identity, transport, and capabilities. - [API versioning and deprecation policy](https://www.flowercomputer.com/api/versioning.md) — Stability, notice, and retirement conventions. - [RSS feed](https://www.flowercomputer.com/rss.xml) — Newly published writing. - [Sitemap](https://www.flowercomputer.com/sitemap-index.xml) — Complete crawl index. - [Product documentation](https://docs.flowercomputer.com/llms.txt) — Bog and Fold documentation index. ## Content policy Public content is available for search, AI input, citation, and model training. See robots.txt for the canonical machine-readable policy.