Find and compare the best Artificial Intelligence software for Zep in 2024
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Use the comparison tool below to compare the top Artificial Intelligence software for Zep on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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n8n
n8n
$20 per monthBuild complex automations up to 10x faster without battling APIs. The days of slogging through a mess of scripts is over. JavaScript is the best choice when you want flexibility, and UI for all other tasks. n8n lets you build flexible workflows that are focused on deep data integration. With a user-friendly interface and templates that can be shared, even the less technically minded members of your team can work together on them. Contrary to other tools, complexity does not limit you. You can build anything you want, without worrying about budget. Connect APIs without code to automate basic functions. You can also use vanilla Javascript to manipulate complex data. You can implement more than one trigger. You can branch and merge your workflows. You can even pause flows while you wait for external events. Custom HTTP requests allow you to easily interface with any API or service. Separate dev and production environments with different sets of authentication data to avoid breaking live workflows. -
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Flowise
Flowise
FreeFlowise is open source and will always be free to use for commercial and private purposes. Build LLMs apps easily with Flowise, an open source UI visual tool to build your customized LLM flow using LangchainJS, written in Node Typescript/Javascript. Open source MIT License, see your LLM applications running live, and manage component integrations. GitHub Q&A using conversational retrieval QA chains. Language translation using LLM chains with a chat model and chat prompt template. Conversational agent for chat model that uses chat-specific prompts. -
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LlamaIndex
LlamaIndex
LlamaIndex, a "dataframework", is designed to help you create LLM apps. Connect semi-structured API data like Slack or Salesforce. LlamaIndex provides a flexible and simple data framework to connect custom data sources with large language models. LlamaIndex is a powerful tool to enhance your LLM applications. Connect your existing data formats and sources (APIs, PDFs, documents, SQL etc.). Use with a large-scale language model application. Store and index data for different uses. Integrate downstream vector stores and database providers. LlamaIndex is a query interface which accepts any input prompts over your data, and returns a knowledge augmented response. Connect unstructured data sources, such as PDFs, raw text files and images. Integrate structured data sources such as Excel, SQL etc. It provides ways to structure data (indices, charts) so that it can be used with LLMs. -
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StepFunction
StepFunction
Our ML engine learns from all customer interactions. StepFunction provides actionable analytics and growth forecasts. Our end-to-end solution adapts to your current state. Growth AI begins with the ingesting of operational data from various systems, including CRM, billing, care/support and product usage. Data preparation is key to step function improvement in business forecasts. StepFunction works with your existing systems of record and doesn't interfere with customer success workflows. Deep dive into your revenue to account new, stable, downgrades and churn. Just a click away are historical trends and future predictions for each cohort. You can get insights in the form risk scores that will allow you to target customers with high scores and recommend actions for treatment. Find out how your customer risk is changing instantly and, most importantly, why it's changing. -
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LangChain
LangChain
We believe that the most effective and differentiated applications won't only call out via an API to a language model. LangChain supports several modules. We provide examples, how-to guides and reference docs for each module. Memory is the concept that a chain/agent calls can persist in its state. LangChain provides a standard interface to memory, a collection memory implementations and examples of agents/chains that use it. This module outlines best practices for combining language models with your own text data. Language models can often be more powerful than they are alone.
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