Neuralhub Alternatives

Streamline deep learning development with a unified platform for building, tuning, and training neural networks, featuring a collaborative community and free compute resources.
Humanloop screenshot thumbnail

Humanloop

If you're looking for another Neuralhub, Humanloop could be a good fit. It's a service designed to oversee and optimize the development of large language models (LLMs), a common challenge with workflows that can be slow and laborious and with human evaluation that can be time-consuming and unreliable. Humanloop has a collaborative prompt management system, an evaluation and monitoring tool, and customization options for integrating private data and fine-tuning models. It integrates with common LLM suppliers and has Python and TypeScript software development kits for integration. It's good for product teams, developers and anyone else building AI features.

Abacus.AI screenshot thumbnail

Abacus.AI

Another good Neuralhub alternative is Abacus.AI. It's a service that lets developers create and run applied AI agents and systems at scale, using generative AI and other neural network technology. Abacus.AI has a range of products, including ChatLLM for creating full-stack RAG systems, AI Agents for automating complex processes, and predictive and analytical tools like forecasting and anomaly detection. It's designed for high availability, governance and compliance, so it's geared for enterprise use.

LastMile AI screenshot thumbnail

LastMile AI

If you're interested in generative AI, LastMile AI is a full-featured platform designed to help engineers bring generative AI projects into production with confidence. It includes tools like Auto-Eval for detecting hallucinations and RAG Debugger for optimizing performance, and AIConfig for versioning and prompt optimization. LastMile AI also has a notebook-like environment for prototyping and supports a range of AI models across different modalities, which makes it easier to deploy production-ready AI applications.

Klu screenshot thumbnail

Klu

Last, you could look at Klu, which is geared for building, deploying and optimizing generative AI applications using large language models like GPT-4 and Llama 2. Klu is designed for fast iteration, built-in analytics and custom model support, so AI engineers and teams can optimize their LLM-based apps more easily. The service has tiered pricing to accommodate different customers, from solo developers to enterprise teams.

More Alternatives to Neuralhub

Dataloop screenshot thumbnail

Dataloop

Unify data, models, and workflows in one environment, automating pipelines and incorporating human feedback to accelerate AI application development and improve quality.

Athina screenshot thumbnail

Athina

Experiment, measure, and optimize AI applications with real-time performance tracking, cost monitoring, and customizable alerts for confident deployment.

ThirdAI screenshot thumbnail

ThirdAI

Run private, custom AI models on commodity hardware with sub-millisecond latency inference, no specialized hardware required, for various applications.

Airtrain AI  screenshot thumbnail

Airtrain AI

Experiment with 27+ large language models, fine-tune on your data, and compare results without coding, reducing costs by up to 90%.

Keywords AI screenshot thumbnail

Keywords AI

Streamline AI application development with a unified platform offering scalable API endpoints, easy integration, and optimized tools for development and monitoring.

Dify screenshot thumbnail

Dify

Build and run generative AI apps with a graphical interface, custom agents, and advanced tools for secure, efficient, and autonomous AI development.

HoneyHive screenshot thumbnail

HoneyHive

Collaborative LLMOps environment for testing, evaluating, and deploying GenAI applications, with features for observability, dataset management, and prompt optimization.

Together screenshot thumbnail

Together

Accelerate AI model development with optimized training and inference, scalable infrastructure, and collaboration tools for enterprise customers.

MLflow screenshot thumbnail

MLflow

Manage the full lifecycle of ML projects, from experimentation to production, with a single environment for tracking, visualizing, and deploying models.

TeamAI screenshot thumbnail

TeamAI

Collaborative AI workspaces unite teams with shared prompts, folders, and chat histories, streamlining workflows and amplifying productivity.

Google AI screenshot thumbnail

Google AI

Unlock AI-driven innovation with a suite of models, tools, and resources that enable responsible and inclusive development, creation, and automation.

Obviously AI screenshot thumbnail

Obviously AI

Automate data science tasks to build and deploy industry-leading predictive models in minutes, without coding, for classification, regression, and time series forecasting.

Parallel AI screenshot thumbnail

Parallel AI

Select and integrate top AI models, like GPT4 and Mistral, to create knowledgeable AI employees that optimize workflow and boost productivity.

Braintrust screenshot thumbnail

Braintrust

Unified platform for building, evaluating, and integrating AI, streamlining development with features like evaluations, logging, and proxy access to multiple models.

Eden AI screenshot thumbnail

Eden AI

Access hundreds of AI models through a unified API, easily switching between providers while optimizing costs and performance.

Freeplay screenshot thumbnail

Freeplay

Streamline large language model product development with a unified platform for experimentation, testing, monitoring, and optimization, accelerating development velocity and improving quality.

Openlayer screenshot thumbnail

Openlayer

Build and deploy high-quality AI models with robust testing, evaluation, and observability tools, ensuring reliable performance and trustworthiness in production.

LLMStack screenshot thumbnail

LLMStack

Build sophisticated AI applications by chaining multiple large language models, importing diverse data types, and leveraging no-code development.

MindStudio screenshot thumbnail

MindStudio

Create custom AI applications and automations without coding, combining models from various sources to boost productivity and efficiency.

MonsterGPT screenshot thumbnail

MonsterGPT

Fine-tune and deploy large language models with a chat interface, simplifying the process and reducing technical setup requirements for developers.