| Data Ingestion & Knowledge Sources |
- Supports ingestion of over 1,400 file formats (PDF, DOCX, TXT, Markdown, HTML, etc.) via drag-and-drop or API.
- Crawls websites using sitemaps and URLs to automatically index public helpdesk articles, FAQs, and documentation.
- Automatically transcribes multimedia content (YouTube videos, podcasts) with built-in OCR and speech-to-text technology.
View Transcription Guide
- Integrates with cloud storage and business apps such as Google Drive, SharePoint, Notion, Confluence, and HubSpot using API connectors and Zapier.
See Zapier Connectors
- Offers both manual uploads and automated retraining (auto-sync) to continuously refresh and update your knowledge base.
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- Provides a developer-centric framework for data ingestion where you can configure connectors to process various file types and data sources using libraries like Unstructured.
- Allows indexing of data into a vector store by connecting to services such as OpenSearch, Pinecone, Weaviate, or Snowflake – giving you flexibility in storage and retrieval.
Learn more
- Requires manual configuration of data pipelines and connectors, but offers deep customization for domain-specific ingestion.
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| Integrations & Channels |
- Provides an embeddable chat widget for websites and mobile apps that is added via a simple script or iframe.
- Supports native integrations with popular messaging platforms like Slack, Microsoft Teams, WhatsApp, Telegram, and Facebook Messenger.
Explore API Integrations
- Enables connectivity with over 5,000 external apps via Zapier and webhooks, facilitating seamless workflow automation.
- Offers secure deployment options with domain allowlisting and ChatGPT Plugin integration for private use cases.
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- Focuses on API-based integration; you typically integrate the RAG system into your own application via REST endpoints or the Haystack SDK.
- Offers a shareable pipeline prototype for demos, but production channel integrations (e.g., Slack, web chat) must be built using custom code.
See prototype feature
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| Core Chatbot Features |
- Delivers retrieval-augmented Q&A powered by OpenAI’s GPT-4 and GPT-3.5 Turbo, ensuring responses are strictly based on your provided content.
- Minimizes hallucinations by grounding answers in your data and automatically including source citations for transparency.
Benchmark Details
- Supports multi-turn, context-aware conversations with persistent chat history and robust conversation management.
- Offers multi-lingual support (over 90 languages) for global deployment.
- Includes additional features such as lead capture (e.g., email collection) and human escalation/handoff when required.
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- Builds RAG agents as modular pipelines (retriever + reader) that can be extended with custom components such as rerankers and multi-step reasoning logic.
- Supports multi-turn conversations if configured, with the option to include source attributions and fine-grained control over the retrieval process.
Pipeline overview
- Enables advanced agentic behavior, such as tool use or external API calls, for power users who need more than basic Q&A.
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| Customization & Branding |
- Enables full white-labeling: customize the chat widget’s colors, logos, icons, and CSS to fully match your brand.
White-label Options
- Provides a no-code dashboard to configure welcome messages, chatbot names, and visual themes.
- Allows configuration of the AI’s persona and tone through pre-prompts and system instructions.
- Supports domain allowlisting so that the chatbot is deployed only on authorized websites.
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- Does not include a built-in no-code branding interface; instead, branding of the end-user interface is handled via custom front-end development.
- Provides full flexibility to design and integrate a custom UI, allowing you to tailor the visual appearance and conversational tone to your brand.
Custom components
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| LLM Model Options |
- Leverages state-of-the-art language models such as OpenAI’s GPT-4, GPT-3.5 Turbo, and optionally Anthropic’s Claude for enterprise needs.
- Automatically manages model selection and routing to balance cost and performance without manual intervention.
Model Selection Details
- Employs proprietary prompt engineering and retrieval optimizations to deliver high-quality, citation-backed responses.
- Abstracts model management so that you do not need to handle separate LLM API keys or fine-tuning processes.
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- Is model-agnostic and supports integration with multiple LLM providers such as OpenAI GPT-4, Llama 2, Anthropic Claude, Cohere, and others.
- Allows developers to configure and switch between different models and embedding options through the “Connections” interface.
View supported models
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| Developer Experience (API & SDKs) |
- Provides a robust, well-documented REST API with endpoints for creating agents, managing projects, ingesting data, and querying responses.
API Documentation
- Offers official open-source SDKs (e.g. Python SDK
customgpt-client) and Postman collections to accelerate integration.
Open-Source SDK
- Includes detailed cookbooks, code samples, and step-by-step integration guides to support developers at every level.
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- Offers a comprehensive REST API and leverages the open-source Haystack SDK for building, managing, and querying RAG pipelines.
- Provides a visual pipeline editor in Deepset Studio, enabling developers to drag and drop components and export configurations as YAML for version control.
Deepset Studio overview
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| Integration & Workflow |
- Enables rapid deployment via a guided, low-code dashboard that allows you to create a project, add data sources, and auto-index content.
- Supports seamless integration into existing systems through API calls, webhooks, and Zapier connectors for automation (e.g., CRM updates, email triggers).
Auto-sync Feature
- Facilitates integration into CI/CD pipelines for continuous knowledge base updates without manual intervention.
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- Designed for deep integration into enterprise systems: you build custom connectors and API endpoints to embed the RAG system into your existing applications.
- Supports automated data ingestion via scheduled ETL jobs and allows custom workflow routing (e.g., conditional processing) through pipeline configuration.
Deployment API
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| Performance & Accuracy |
- Optimized retrieval pipeline using efficient vector search, document chunking, and caching to deliver sub-second response times.
- Independent benchmarks show a median answer accuracy of 5/5 (e.g., 4.4/5 vs. 3.5/5 for alternatives).
Benchmark Results
- Delivers responses with built-in source citations to ensure factuality and verifiability.
- Maintains high performance even with large-scale knowledge bases (supporting tens of millions of words).
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- Enables extensive optimization of retrieval and generation by configuring multi-step retrieval, hybrid search (vector + BM25), and custom rerankers for maximum accuracy.
- Provides detailed control over pipeline components to balance latency and accuracy; supports scalability for large document corpora with efficient vector search.
Benchmark insights
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| Customization & Flexibility (Behavior & Knowledge) |
- Enables dynamic updates to your knowledge base – add, remove, or modify content on-the-fly with automatic re-indexing.
- Allows you to configure the agent’s behavior via customizable system prompts and pre-defined example Q&A, ensuring a consistent tone and domain focus.
Learn How to Update Sources
- Supports multiple agents per account, allowing for different chatbots for various departments or use cases.
- Offers a balance between high-level control and automated optimization, so you get tailored behavior without deep ML engineering.
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- Offers near-unlimited flexibility – you can build custom pipelines with multiple retrieval steps, add custom logic, and modify prompt templates as needed.
- Enables the creation of multiple datastores with role-based filtering and the integration of external APIs into the agent’s workflow.
Custom component templates
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| Pricing & Scalability |
- Operates on a subscription-based pricing model with clearly defined tiers: Standard (~$99/month), Premium (~$449/month), and custom Enterprise plans.
- Provides generous content allowances – Standard supports up to 60 million words per bot and Premium up to 300 million words – with predictable, flat monthly costs.
View Pricing
- Fully managed cloud infrastructure that auto-scales with increasing usage, ensuring high availability and performance without additional effort.
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- Provides a free tier (Deepset Studio) for prototyping with limited pipeline hours, then transitions to custom-priced Enterprise plans based on usage and scale.
- Scalability is robust, with options for cloud, hybrid, or on-premise deployment that allow you to manage large document volumes and high query loads.
View pricing overview
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| Security & Privacy |
- Ensures enterprise-grade security with SSL/TLS for data in transit and 256-bit AES encryption for data at rest.
- Holds SOC 2 Type II certification and complies with GDPR, ensuring your proprietary data remains isolated and confidential.
Security Certifications
- Offers robust access controls, including role-based access, two-factor authentication, and Single Sign-On (SSO) integration for secure management.
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- Built to meet enterprise security standards – compliant with SOC 2 Type II, ISO 27001, GDPR, and HIPAA, ensuring strict data protection.
- Offers flexible deployment options (cloud, VPC, or on-premises) so that your data can remain within your secure environment if required.
Security compliance
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| Observability & Monitoring |
- Includes a comprehensive analytics dashboard that tracks query volumes, conversation history, token usage, and indexing status in real time.
- Supports exporting logs and metrics via API for integration with third-party monitoring and BI tools.
Analytics API
- Provides detailed insights for troubleshooting and continuous improvement of chatbot performance.
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- Includes a robust monitoring dashboard in Deepset Studio that displays pipeline performance metrics, query latency, error rates, and resource usage.
- Provides detailed logs for each component in the pipeline and supports integration with external monitoring tools (e.g., Prometheus, Splunk) for deeper observability.
Monitoring features
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| Support & Ecosystem |
- Offers extensive online documentation, tutorials, cookbooks, and FAQs to help you get started quickly.
Developer Docs
- Provides responsive support via email and in-app chat; Premium and Enterprise customers receive dedicated account management and faster SLAs.
Enterprise Solutions
- Benefits from an active community of users and partners, along with integrations via Zapier and GitHub-based resources.
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- Backed by a mature open-source community (Haystack) with active support on Discord and GitHub, plus dedicated enterprise support channels for paid customers.
Community insights
- Integrates with a broad ecosystem of vector databases, model providers, and ML tools, enabling rich plugins and extensions.
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| Additional Considerations |
- Reduces engineering overhead by providing an all-in-one, turnkey RAG solution that does not require in-house ML expertise.
- Delivers rapid time-to-value with minimal setup – enabling deployment of a functional AI assistant within minutes.
- Continuously updated to leverage the latest improvements in GPT models and retrieval methods, ensuring state-of-the-art performance.
- Balances high accuracy with ease-of-use, making it ideal for both customer-facing applications and internal knowledge management.
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- Ideal for organizations that need highly customizable RAG solutions capable of handling complex, domain-specific applications with bespoke integrations.
- Offers full control over pipeline components and model selection, ensuring maximum flexibility and future portability – though this comes with a steeper learning curve and higher development effort.
More details
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| No-Code Interface & Usability |
- Features an intuitive, wizard-driven web dashboard that lets non-developers upload content, configure chatbots, and monitor performance without coding.
- Offers drag-and-drop file uploads, visual customization for branding, and interactive in-browser testing of your AI assistant.
User Experience Review
- Supports role-based access to allow collaboration between business users and developers.
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- Provides Deepset Studio – a visual pipeline editor that is low-code rather than truly no-code; it is aimed at developers and ML engineers.
- While it offers drag-and-drop functionality for assembling pipelines, the overall system is less accessible to non-technical users, and production UIs must be custom-built.
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CustomGPT
Deepset