Meet Chorus. We extended Zed Industries open-source IDE to make it an integrated agent environment. It complements sing, the open-source, GraalVM native binary that provisions bare-metal servers and creates fully isolated development environments. Contributions welcome!
singular™
Technology, Information and Internet
Austin, Texas 430 followers
Critical Software. Delivered with Precision. Accelerated by AI.
About us
Our company operates like a Forward-Deployed strike team for startups and fortune 500 companies. When a company has a critical software or AI system to build, specifically in complex and highly regulated industries like healthcare or finance, we assemble a two-to-three person team to take it from architecture to deployment. And we do this with extreme velocity and engineering rigor. So no agency bloat, delays, and absolutely no slop. Our specialties include: • AI-Native Platform Development • Composable Enterprise Architecture • Regulated & Compliant Systems (GxP, HIPAA) • High-Performance Software Engineering • Mobile & Web Development Visit our website to see our work and learn about our approach.
- Website
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https://singlr.ai/
External link for singular™
- Industry
- Technology, Information and Internet
- Company size
- 2-10 employees
- Headquarters
- Austin, Texas
- Type
- Privately Held
- Specialties
- Artificial Intelligence, Machine Learning, SaaS, B2B, Software, Agentic Workflows, and iOS/Android
Locations
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Primary
Get directions
Austin, Texas , US
Employees at singular™
Updates
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sing is a single native binary compiled with GraalVM on JDK 25. Now comes with a Mac thin client. Each project gets its own Incus system container with rootless Podman for services. The container is derived state. Destroy and rebuild whenever you want. Open source, MIT licensed. github.com/singlr-ai/sing
Been using BDD/spec-driven development with sing for my personal finance project. Brainstorm the spec during the day with the agent, "sing dispatch" at night, review the PR in the morning. sing snapshots the container, and launches the agent. Agent picks the next ready spec, creates a branch, and gets going. The spec board tracks what's done, what's in progress, and what depends on what. 5 feed integrations built this way so far. The agent is working through the queue.
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A month ago we posted that Singular engineers use "sing" to run fully isolated AI agent environments on bare metal. A few people asked if we'd open-source it. We did. sing is a CLI that provisions bare-metal servers and creates fully isolated dev environments for agentic workflows. What's new since that post: - Spec-driven dispatch. Write the spec during the day, the agent executes it overnight, review results in the morning. - Cross-agent orchestration. Claude Code builds, Codex reviews — or the other way around. - Guardrails enforced from the host. Wall-clock limits, idle detection, commit monitoring. Outside the agent's container, outside its reach. - Context generation. CLAUDE.md, AGENTS.md, SECURITY.md generated from your project config. Same architecture underneath: Incus system containers, rootless Podman, cgroup isolation, declarative YAML. The container is derived state. The config is source of truth. Destroy and rebuild at-will. One native binary. Zero dependencies. MIT licensed.
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Composable Enterprise.
Last week I described the SaaS Sprawl problem. A patient in seven databases. An S3 bucket open for three days. It resonated with some folks. I ended with: Agentic Periphery, Deterministic Core. Here is what that means. Agents do the analysis. They crawl data, cross-reference records, flag anomalies, and produce structured findings. They do real work. But they are structurally barred from changing anything. No database writes. No transactions. No state changes. Every finding hits a verification gate before it reaches execution. If the gate rejects it, the finding dies. If it passes, strict deterministic code handles the write. This is an architectural constraint. The non-deterministic layer cannot reach the execution layer without passing through deterministic validation. Why it matters: the failure mode of every AI enterprise product right now is the same. A language model guesses, and the guess reaches production. In healthcare that is a wrong diagnosis. In finance that is a bad trade. In compliance that is a report full of hallucinated evidence. One thing we noticed while building this: when the execution layer is actually trustworthy, the interface calms down. You need fewer confirmation dialogs and fewer warning banners. The system can show you a clean queue of decisions instead of a wall of alerts. Make the call, move on. We are calling that cognitive relief. Still figuring out if the term is good or pretentious. Probably both. More soon.
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singular™ reposted this
A mid-size hospital runs Epic for EHR, Medidata for clinical trials, Workday for HR, NetSuite for finance, Salesforce for donor relations, Jira for IT tickets, and fifteen more. Each system has its own data model, its own auth, its own API. A patient exists in seven databases and none of them agree on spelling. Compliance teams at banks run Drata for SOC2, Vanta for vendor risk, ServiceNow for IT governance, Splunk for log monitoring, and a spreadsheet someone made in 2019 that nobody wants to touch but everyone depends on. An engineer opens an S3 bucket to the public. It takes three days and four tools for anyone to notice. Every Startup or enterprise is running 100+ SaaS applications held together with API wrappers, Zaps, and manual processes. The data is fragmented. The logic is duplicated. The security surface grows with every vendor contract. Adding AI to this mess just creates smarter fragments. This is SaaS Sprawl. It is the default state of every company we have worked with. There's a better way. Agentic Periphery, Deterministic Core. More soon.
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Running 4-6 client projects simultaneously on a laptop is a challenge. Docker isolation is a shared kernel with a nice namespace wrapper. When you have AI coding agents running autonomously across projects, each needing their own runtimes, databases, and search engines, that's not good enough. Singular engineers use Sing, our new internal CLI. Full Linux system containers on bare metal via Incus. Rootless Podman for services. Declarative YAML. A native binary compiled with GraalVM. Each project gets its own isolated environment, with agentic tools like Claude Code, and can run whatever stack it needs. No AI in the tool. Deterministic infrastructure. The agents run inside the sandboxes Sing creates, not as part of it. Has been a real throughput multiplier for us!
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singular™ reposted this
Agent-powered software engineering feels like F1 racing now. The Model (Opus/Gemini/OSS) is the driver. Raw speed, rapid correction. REPL, compilation & error logs are the feedback system. Just as a driver feels tire slip and adjusts mid-corner, the model needs high-fidelity execution data to self-correct in real-time. The software engineer is the race strategist. If we let the driver lap blindly, they will crash. Our job is to optimize the spec, tune the feedback loops, and manage resources. Agentic loops (like the brute force "Ralph Wiggum" pattern) make this possible. Simple is sophisticated.
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