Best Artificial Intelligence Software for Openlayer - Page 2

Compare the Top Artificial Intelligence Software that integrates with Openlayer as of October 2026 - Page 2

This a list of Artificial Intelligence software that integrates with Openlayer. Use the filters on the left to add additional filters for products that have integrations with Openlayer. View the products that work with Openlayer in the table below.

  • 1
    Portkey

    Portkey

    Portkey.ai

    Launch production-ready apps with the LMOps stack for monitoring, model management, and more. Replace your OpenAI or other provider APIs with the Portkey endpoint. Manage prompts, engines, parameters, and versions in Portkey. Switch, test, and upgrade models with confidence! View your app performance & user level aggregate metics to optimise usage and API costs Keep your user data secure from attacks and inadvertent exposure. Get proactive alerts when things go bad. A/B test your models in the real world and deploy the best performers. We built apps on top of LLM APIs for the past 2 and a half years and realised that while building a PoC took a weekend, taking it to production & managing it was a pain! We're building Portkey to help you succeed in deploying large language models APIs in your applications. Regardless of you trying Portkey, we're always happy to help!
    Starting Price: $49 per month
  • 2
    Amazon Bedrock
    Amazon Bedrock is a fully managed service that simplifies building and scaling generative AI applications by providing access to a variety of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself. Through a single API, developers can experiment with these models, customize them using techniques like fine-tuning and Retrieval Augmented Generation (RAG), and create agents that interact with enterprise systems and data sources. As a serverless platform, Amazon Bedrock eliminates the need for infrastructure management, allowing seamless integration of generative AI capabilities into applications with a focus on security, privacy, and responsible AI practices.
  • 3
    Palantir AIP
    Deploy LLMs and other AI — commercial, homegrown or open-source — on your private network, based on an AI-optimized data foundation. AI Core is a real-time, full-fidelity representation of your business that includes all actions, decisions, and processes. Utilize the Action Graph, atop the AI Core, to set specific scopes of activity for LLMs and other models – including hand-off procedures for auditable calculations and human-in-the-loop operations. Monitor and control LLM activity and reach in real-time to help users promote compliance with legal, data sensitivity, and regulatory audit requirements.
  • 4
    Groq

    Groq

    Groq

    GroqCloud is a high-performance AI inference platform built specifically for developers who need speed, scale, and predictable costs. It delivers ultra-fast responses for leading generative AI models across text, audio, and vision workloads. Powered by Groq’s purpose-built LPU (Language Processing Unit), the platform is designed for inference from the ground up, not adapted from training hardware. GroqCloud supports popular LLMs, speech-to-text, text-to-speech, and image-to-text models through industry-standard APIs. Developers can start for free and scale seamlessly as usage grows, with clear usage-based pricing. The platform is available in public, private, or co-cloud deployments to match different security and performance needs. GroqCloud combines consistent low latency with enterprise-grade reliability.
  • 5
    Azure AI Content Understanding
    Azure AI Content Understanding helps enterprises transform unstructured multimodal data into insights. Derive meaningful insights from diverse types of input data, ranging from text, audio, images, and video. Achieve precise, high-quality data for downstream applications with sophisticated AI methods such as scheme extraction and grounding. Streamline and unify pipelines of varied data types into a single streamlined workflow, reducing overall costs and accelerating time to value. See how businesses and call center operators generate valuable insights from call recordings to track essential KPIs, enhance product experiences, and respond to customer inquiries more swiftly and accurately. Ingest a range of modalities, such as documents, images, audio, or video, and use a range of AI models available in Azure AI to transform input data into structured output that can be easily processed and analyzed by downstream applications.
  • 6
    Langflow

    Langflow

    Langflow

    Langflow is a low-code AI builder designed to create agentic and retrieval-augmented generation applications. It offers a visual interface that allows developers to construct complex AI workflows through drag-and-drop components, facilitating rapid experimentation and prototyping. The platform is Python-based and agnostic to any model, API, or database, enabling seamless integration with various tools and stacks. Langflow supports the development of intelligent chatbots, document analysis systems, and multi-agent applications. It provides features such as dynamic input variables, fine-tuning capabilities, and the ability to create custom components. Additionally, Langflow integrates with numerous services, including Cohere, Bing, Anthropic, HuggingFace, OpenAI, and Pinecone, among others. Developers can utilize pre-built components or code their own, enhancing flexibility in AI application development. The platform also offers a free cloud service for quick deployment and test
  • 7
    Open WebUI

    Open WebUI

    Open WebUI

    Open WebUI is an extensible, feature-rich, and user-friendly self-hosted AI platform designed to operate entirely offline. It supports various LLM runners like Ollama and OpenAI-compatible APIs, with a built-in inference engine for Retrieval Augmented Generation (RAG), making it a powerful AI deployment solution. Key features include effortless setup via Docker or Kubernetes, seamless integration with OpenAI-compatible APIs, granular permissions and user groups for enhanced security, responsive design across devices, and full Markdown and LaTeX support for enriched interactions. Additionally, Open WebUI offers a Progressive Web App (PWA) for mobile devices, providing offline access and a native app-like experience. The platform also includes a Model Builder, allowing users to create custom models from base Ollama models directly within the interface. With over 156,000 users, Open WebUI is a versatile solution for deploying and managing AI models in a secure, offline environment.
  • 8
    Unity AI Gateway
    Unity AI Gateway provides centralized governance, observability, and spend controls across enterprise AI systems, helping organizations manage agents, tools, models, MCPs, and AI frameworks from a single governed layer. It applies consistent governance across Databricks-hosted AI, external models, coding agents, agent harnesses, and other AI services without locking teams into a single provider or stack. Identity-aware policies control what agents can access, which actions they can take, and which tools they can use, while built-in, custom, and third-party guardrails enforce safety and compliance across prompts, responses, and interactions. It captures prompts, traces, tool calls, payload logs, audit logs, token usage, and policy decisions to monitor behavior, investigate incidents, and support compliance. Centralized cost controls track consumption across users, teams, applications, agents, and providers, with budgets, rate limits, and hard spend caps.