| 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 highly scalable, developer-controlled ingestion pipeline supporting over 40+ file formats (PDFs, spreadsheets, audio, etc.) for massive data volumes.
Reference
- Supports asynchronous ingestion with auto-scaling, capable of processing millions of tokens per second – ideal for enterprise-scale corpora.
Benchmark details
- Developers can ingest data via code or API, allowing integration with proprietary databases and custom pipelines.
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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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- Exposes a RESTful RAG API that developers can integrate into any channel – websites, mobile apps, internal tools, or legacy systems.
- Does not offer pre-built chat widgets; channel connectors are built by the developer for custom integrations.
API snippet example
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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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- Provides a core RAG engine for retrieval-augmented answers, with support for multi-turn dialogues if integrated into a custom UI.
- Supports multi-lingual deployments depending on the underlying LLM configuration; model choice determines language capabilities.
- Allows developers to design custom lead capture and human handoff workflows through the API.
See use case
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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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- Delivers a fully bespoke solution where the chatbot’s UI and behavior are custom-built to match the client’s brand identity.
- Since SciPhi is backend-focused, any front-end branding is handled separately by developers, offering complete freedom.
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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 LLM-agnostic – supports multiple providers such as OpenAI’s GPT-4, Anthropic’s Claude, and various open-source models (e.g. Llama 2).
- Allows developers to select, fine-tune, or switch between models based on project needs, providing full control over performance and cost.
View model options
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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 RESTful API and a Python client library (
R2RClient) that abstracts core functions such as document ingestion and query retrieval.
Python SDK example
- Documentation and GitHub repositories provide deep technical details and open-source access for customization.
SciPhi GitHub
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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 as a microservice, SciPhi can be integrated into existing enterprise workflows (e.g. document pipelines, CRM systems) via its API.
- Enables custom workflow automation such as triggering ERP actions or support ticket creation on query escalation.
See integration overview
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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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- Optimized for high-speed, high-throughput retrieval with hybrid search combining dense vector and keyword filtering.
- Integrates knowledge graphs for enhanced context and can achieve up to 150% improvement in accuracy with HybridRAG.
Benchmark details
- Latency remains low even at enterprise scale, with responses typically delivered within hundreds of milliseconds.
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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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- Provides full programmability for integrating new data sources, adjusting retrieval parameters, and combining multiple collections.
- Allows developers to implement custom dialog flows, re-rank retrieved documents, and even chain multiple API calls for agentic behavior.
See customizability
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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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- Offers a Free tier and a low-cost Dev tier (starting at ~$25/month) with limited RAG requests and file limits – ideal for experimentation.
- Enterprise plans are available with custom pricing and self-hosting options, allowing for scalable, high-volume deployments.
View SciPhi pricing
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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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- When used via SciPhi Cloud, data is isolated per customer; for maximum privacy, self-hosting enables complete control over data storage.
- Provides standard encryption in transit and at rest; self-hosted deployments can be configured to meet strict regulatory requirements.
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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 developer dashboard with real-time logs, detailed performance metrics, and analytics on query latency and retrieval quality.
Dashboard on GitHub
- Supports integration with external monitoring tools (e.g., Prometheus, Grafana) for comprehensive observability.
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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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- Provides community support via Discord and GitHub issues, with dedicated support for Enterprise customers and detailed technical documentation.
SciPhi Support
- As an open-source platform, fosters a community of developers contributing improvements and integrations.
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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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- Offers advanced innovations such as automatic knowledge graph construction (GraphRAG) and potential for agentic RAG behaviors for multi-step reasoning.
Learn about GraphRAG
- Provides full control over the pipeline, making it ideal for enterprises that need bespoke, integrated AI solutions with maximum flexibility.
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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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- Does not provide a no-code, end-user interface; the system is primarily designed for developers to integrate into custom UIs.
- The provided dashboard is utilitarian, geared toward testing and monitoring rather than general business user management.
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