Humanloop

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Humanloop helps teams build and manage AI features, ensuring secure, efficient collaboration and seamless production integration.

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What is Humanloop?

Humanloop is a collaborative platform designed for building AI features where Product Managers, Engineers, and Domain Experts can work together efficiently. It facilitates managing and iterating on prompts across an organization, offers an evaluation and monitoring suite for debugging prompts before production, and provides customization and optimization tools to enhance model performance by connecting private data. Humanloop allows easy integration into production applications, with version-controlled prompts and deployment capabilities executed by PMs or within existing CI/CD systems. The platform combines software best practices with the requirements of Large Language Models (LLMs), empowering entire teams to contribute to AI improvement effectively. Humanloop aims to enable the safe and secure adoption of AI throughout an organization, ensuring data privacy and security while providing end-to-end monitoring and support from AI experts. The team behind Humanloop consists of professionals with previous experience at major tech companies like Google, Microsoft, and Amazon, and the platform supports various models including OpenAI, Anthropic, Llama2, and custom models.

Who created Humanloop?

Humanloop was founded by Raza Habib, who serves as the CEO. Raza previously worked at MonolithAI and Google, holding a Ph.D. in Machine Learning from UCL and an MSc in Physics from Cambridge. The company's team includes experts from prestigious backgrounds like Google, Microsoft, and Amazon, with substantial support from investors like Index Ventures and Y Combinator.

What is Humanloop used for?

Collaborative playground with history
Prompt management and deployment controls
Backtest changes and confidently update models
Capture feedback and run quantitative experiments
Manage and iterate on prompts across your organization
Debug prompts, chains, or agents before shipping to production
Connect private data and fine-tune for differentiated model performance
Enable domain experts to contribute to prompt engineering
End-to-end monitoring of AI applications
Adopt best practices and share learnings throughout the organization

How to use Humanloop?

To use Humanloop, follow these steps:

Collaboration: Humanloop allows PMs, Engineers, and Domain Experts to collaborate on building AI features in a shared workspace with history and deployment controls.
Prompt Management: Manage and iterate on prompts across your organization within the platform.
Evaluation and Monitoring Suite: Debug prompts, chains, or agents before deploying to production by defining metrics and integrating into workflows.
Customization and Optimization: Connect private data, fine-tune models, and integrate with existing CI/CD systems for improved performance.
Developers Integration: Easily integrate Humanloop into production applications with version controlled prompts and flexible deployment options.
Enterprise Adoption: Safely deploy AI throughout your organization with a focus on data privacy, security, and shared learnings.
Support and Mission: Gain fast support, end-to-end monitoring, and enable implementation of AI across various domains securely.
Team: Meet the founders and key team members of Humanloop, with expertise from major AI projects and top investors backing the venture.

By following these steps, users can effectively leverage Humanloop for prompt management, evaluation, and collaboration in AI development projects.

Pros

Supported by a team with experience from Google, Microsoft, Amazon, and backed by top investors like Index Ventures and Y Combinator
Facilitates sharing best practices and learnings within the organization
End-to-end monitoring of AI applications with support from trusted AI experts
Enables adoption of AI throughout the organization with safety and security measures
Facilitates management of test data and integration into CI/CD workflows for evaluation
Supports OpenAI, Anthropic, Llama2, and custom models
Empowers domain experts to contribute to prompt engineering in a version-controlled environment
Allows for customization and optimization with private data integration for improved model performance
Offers evaluation and monitoring tools for debugging prompts before production
Provides a collaborative AI playground with history tracking

Cons

Manual evaluation and workflows require high effort
Changes may cause performance regressions
No specific cons or missing features related to value for money mentioned
High effort manual evaluation and workflows
Changes causing performance regressions

Pros

Cons

Supported by a team with experience from Google, Microsoft, Amazon, and backed by top investors like Index Ventures and Y Combinator
Facilitates sharing best practices and learnings within the organization
End-to-end monitoring of AI applications with support from trusted AI experts
Enables adoption of AI throughout the organization with safety and security measures
Facilitates management of test data and integration into CI/CD workflows for evaluation
Supports OpenAI, Anthropic, Llama2, and custom models
Empowers domain experts to contribute to prompt engineering in a version-controlled environment
Allows for customization and optimization with private data integration for improved model performance
Offers evaluation and monitoring tools for debugging prompts before production
Provides a collaborative AI playground with history tracking

Manual evaluation and workflows require high effort
Changes may cause performance regressions
No specific cons or missing features related to value for money mentioned
High effort manual evaluation and workflows
Changes causing performance regressions

Humanloop FAQs

How does the free trial work?: The free trial allows users to test the platform before making a commitment.

How long does it take to setup a working system?: The setup time for a working system depends on various factors and needs to be evaluated on a case-by-case basis.

Do I pay for OpenAI, Anthropic etc. separately?: Payment details for services such as OpenAI and Anthropic should be checked with the respective providers.

What data formats are supported?: The platform likely supports various data formats; specific details can be found in the platform documentation.

Can I use my own model or other providers?: Users may have the option to use their own models or models from other providers; the platform documentation should provide more information.

Is there an option for on-premise deployment?: Details about on-premise deployment options can be provided by the Humanloop team.

What kind of support is available for enterprise customers?: Enterprise customers can expect fast support and end-to-end monitoring of their AI applications.

How does Humanloop ensure data privacy and security?: Humanloop ensures the activation of large language models (LLMs) with private data in a secure manner, putting the customer in control of their data and models.