End-to-end AI solutions, trusted by leading companies.
Huge demo from our Spring release event: Airbyte Connector Builder... now Powered by AI! Check out the video, it's AMAZING!!!
At Airbyte, we pride ourselves on being the data movement platform of the future. Over the past year and a half, we've provided more connectors to enable RAG use cases, published tons of tutorials, made our connectors available in LangChain and we're powering data systems at companies that are defining the future of the AI world.
Now, we're embedding AI directly into our product. The public release is planned for 1.0, and it is just around the corner!
Have been collaborating with these guys on something I get to share soon and HIGHLY recommend them
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Case study
Change.org, the world’s largest platform for social change, enables anyone to start campaigns and mobilize support. With thousands of campaigns launched daily, not all adhere to Change.org's trust and safety terms. Fractional AI partnered with Change.org to automate content moderation, so the team can spend less time reviewing content and more time supporting changemakers.
The Change.org back-office team built an impressive system in Google Sheets that used LLMs to proactively flag half of violations, but finding the other half was still a big drain on time and the site experience.
Fractional AI built an AI-powered content moderation system to automatically review content that violates Change.org’s guidelines.
Models used: GPT 4o, we fine-tuned GPT 3.5 using OpenPipe
Tools used: Langchain, Langsmith
The new system catches 77% of violations while halving the proportion of false positives.
Case study
Airbyte is the leading open-source data integration engine that helps you consolidate your data in your warehouses, lakes, and databases. Airbyte’s users spend a lot of time building API integrations – a complicated and time-intensive process, so Airbyte hired Fractional AI to develop an AI-powered connector builder, producing API integrations in minutes, not hours.
Building API integrations is tedious and complicated.
Engineers have to navigate lengthy API docs, extract relevant details, and manually configure complicated connectors in Airbyte’s tools – all of which takes time away from other engineering projects.
Users input the API docs URL, and the AI Connector Builder, built by Fractional AI, crawls API docs and configures an Airbyte connector.
Models used: GPT 4o, GTP 3.5
Tools used: Langchain, Langsmith, Chroma DB
Time to build an API integration is going from hours to minutes. Stay tuned for the Airbyte launch.
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Case study
Superintelligent is the learning platform for AI, offering tutorials on AI tools that are hands-on, practical, and easy to follow. When debuting their platform, Superintelligent imagined a fully personalized, AI-powered user experience, but where do you start with a project that big? Fractional AI partnered with Superintelligent to build an AI chatbot as the first step towards that vision.
Learners needed a way to quickly navigate the platform’s hundreds of tutorials and tool recommendations to find relevant AI tools for their specific needs.
Fractional AI developed an AI chatbot using RAG to recommend specific tools to learners.
Models used: GPT 4, GPT 3.5 Turbo
Tools used: Langchain, Langsmith, Pinecone, FastAPI
The chatbot has given hundreds of recommendations - eliminating the need for extensive searches, so users can spend less time searching and more time learning.
Case study
Sincera, a technology platform leveraging metadata to enhance adtech solutions, faced a major challenge: a vast stream of unstructured data. Fractional AI partnered with Sincera to build an AI system to normalize and classify this data, unlocking its potential for value creation.
Sincera’s lean team receives millions of unstructured records each month, detailing thousands of distinct products (in CSVs!). The lack of consistency in syntax and structure makes it impossible to use the data without lengthy and tedious standardization efforts.
Fractional AI is developing an AI Product Categorization workflow to map unstructured, arbitrary product data into a clear product taxonomy in real-time.
Models used: GPT-4o-mini, Claude-3.5-sonnet, Llama-3.1
Tools used: Braintrust, Instructor
Fractional AI's system will enable Sincera to confidently process and use messy data from a variety of sources in an automated pipeline without costly human intervention, making the data far more usable than would otherwise be possible.
