🗑️ This startup cleans garbage from LLMs

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Top picks

A quick highlight

Cleanlab

Amount: $25M 🎉

Round: Series A

Lead Investors: Menlo Ventures, TQ Ventures

Cleanlab aims to solve the data problem of “garbage in, garbage out” in AI models.

Their product can automatically label up to 90% of a raw, unlabelled data set on a first pass. It also flags data points and labels it thinks are most likely to be duplicates or errors, helping users scrub it faster and cheaper for a more accurate end result.

Modal

Amount: $16M 🎉

Round: Series A

Lead Investor: Redpoint

Modal Labs provides cloud-based infrastructure to data teams and app developers, particularly those creating generative AI applications.

Its platform allows data teams to easily run Python code in the cloud without infrastructure configuration. Users can deploy autoscaling inference endpoints, run large batch jobs, and convert functions into web endpoints or cron jobs all from Python. Modal handles all the hosting, provisioning, and scaling, allowing engineers to focus on writing code rather than YAML configuration.

SuperOps.ai

Amount: $12.4M 🎉

Round: Series B

Lead Investors: Addition, March Capital

SuperOps.ai’s mission is to simplify the IT management process and workflow of Managed Service Providers (MSPs) on a single platform.

They provide an automation-led unified Professional Services Automation (PSA) and Remote Monitoring and Management (RMM) platform with built-in IT documentation, project management, and a recently launched networking monitoring feature. Their AI framework is advancing into a predictive intelligence layer that will not only help MSPs improve their efficiency but also move from solving client issues to pre-empting them.

minds.ai

Amount: $5.3M 🎉

Round: Seed

Lead Investor: Monta Vista Capital

minds.ai’s mission is to drive innovation in the application of AI in semiconductor manufacturing.

Their Maestro™ end-to-end solution integrates seamlessly into existing workflows, improving the efficiency and productivity of fab manufacturing processes using supervised learning, reinforcement learning, and generative AI.

Tabby

Amount: $3.2M 🎉

Round: Seed

Lead Investors: Zoo Capital, Yunqi Partners

TabbyML’s mission is to create AI assistants that help humans write computer code. They believe in a future where all companies will have some sort of customization demand in software development.

They offer an open-source code generator. It is a self-hosted coding assistant that has the advantage of being highly customizable. Every time users choose not to incorporate TabbyML’s suggestions or make edits to its auto-filled code, the AI model fine-tunes based on that information.

Tidalflow

Amount: $1.7M 🎉

Round: Pre-Seed

Lead Investors: Dig Ventures, Gradient Ventures

Tidalflow provides an end-to-end platform that enables developers to make their existing software play nicely with the LLM ecosystem.

Their plugin lifecycle management platform allows software businesses to develop, test, monitor, and monetize their product instances for compatibility with LLMs, opening new distribution channels and revenue streams.

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