SAIL is a strike team. We design and build critical software and AI systems with two or three senior engineers per engagement, from architecture to deployment. Every dollar is engineering. Every engagement is on the keyboard.
Engagement shape
Weeks to first deploy
Technical debt
Capital to engineering
Validated outcomes
We used to spend months manually reconciling data. Now it happens instantly. In four months, this team built a clinical intelligence platform that cut our trial timelines by 36% . The clarity of AI insights is game-changing.
I've been in deep tech for 15 years, and this team is in a different league. Their precision and mastery were world-class. I almost want to gatekeep them for ourselves.
What we believe
AI is a tool.
Trust is the discipline.
The work is the byline.
Production code.
Day one.
Critical systems.
Cool heads.
Field Intelligence
Engineering notes, research commentary, and lessons from production deployments.
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How Singular uses system containers, rootless Podman, and declarative YAML configs to run isolated, multi-project AI agent environments on a single $50/month bare-metal server.
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Study notes on why LLMs produce different outputs for the same prompt—even at temperature 0—and the batch invariance solutions that achieve 100% reproducibility.
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In this blog post, we will discuss how to fine-tune Llama 2 7B pre-trained model using the PEFT library and QLoRa method. We'll use a custom instructional dataset to build a sentiment analysis model.
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