In this comprehensive guide, we compare SciPhi and SimplyRetrieve across various parameters including features, pricing, performance, and customer support to help you make the best decision for your business needs.
Overview
Welcome to the comparison between SciPhi and SimplyRetrieve!
Here are some unique insights on SciPhi:
SciPhi is an open-source RAG platform that touts massive scale, hybrid search, and auto-generated knowledge graphs. It’s developer-friendly and highly flexible—if you’re ready for the learning curve.
And here's more information on SimplyRetrieve:
SimplyRetrieve is an open-source RAG stack you run on your own hardware. It keeps data in-house and pairs with open-source LLMs, giving developers full visibility into the pipeline.
Expect hands-on setup—GPU drivers, Python deps, scripts—before you’re up and running.
Enjoy reading and exploring the differences between
SciPhi and SimplyRetrieve.
Detailed Feature Comparison
Features
SciPhi
SimplyRetrieve
CustomGPTRECOMMENDED
Data Ingestion & Knowledge Sources
Handles 40 + formats—from PDFs and spreadsheets to audio—at massive scale
Reference.
Async ingest auto-scales, crunching millions of tokens per second—perfect for giant corpora
Benchmark details.
Ingest via code or API, so you can tap proprietary databases or custom pipelines with ease.
Uses a hands-on, file-based flow: drop PDFs, text, DOCX, PPTX, HTML, etc. into a folder and run a script to embed them.
A new GUI Knowledge-Base editor lets you add docs on the fly, but there’s no web crawler or auto-refresh yet.
Lets you ingest more than 1,400 file formats—PDF, DOCX, TXT, Markdown, HTML, and many more—via simple drag-and-drop or API.
Crawls entire sites through sitemaps and URLs, automatically indexing public help-desk articles, FAQs, and docs.
Turns multimedia into text on the fly: YouTube videos, podcasts, and other media are auto-transcribed with built-in OCR and speech-to-text.
View Transcription Guide
Connects to Google Drive, SharePoint, Notion, Confluence, HubSpot, and more through API connectors or Zapier.
See Zapier Connectors
Supports both manual uploads and auto-sync retraining, so your knowledge base always stays up to date.
Integrations & Channels
Ships a REST RAG API—plug it into websites, mobile apps, internal tools, or even legacy systems.
No off-the-shelf chat widget; you wire up your own front end
APIÂ snippet.
Ships with a local Gradio GUI and Python scripts for queries—no out-of-the-box Slack or site widget.
Want other channels? Write a small wrapper that forwards messages to your local chatbot.
Embeds easily—a lightweight script or iframe drops the chat widget into any website or mobile app.
Offers ready-made hooks for Slack, Microsoft Teams, WhatsApp, Telegram, and Facebook Messenger.
Explore API Integrations
Connects with 5,000+ apps via Zapier and webhooks to automate your workflows.
Supports secure deployments with domain allowlisting and a ChatGPT Plugin for private use cases.
Core Chatbot Features
Core RAG engine serves retrieval-grounded answers; hook it to your UI for multi-turn chat.
Multi-lingual if the LLM you pick supports it.
Lead-capture or human handoff flows are yours to build through the API
Use case.
Runs a retrieval-augmented chatbot on open-source LLMs, streaming tokens live in the Gradio UI.
Primarily single-turn Q&A; long-term memory is limited in this release.
Includes a “Retrieval Tuning Module” so you can see—and tweak—how answers are built from the data.
Powers retrieval-augmented Q&A with GPT-4 and GPT-3.5 Turbo, keeping answers anchored to your own content.
Reduces hallucinations by grounding replies in your data and adding source citations for transparency.
Benchmark Details
Handles multi-turn, context-aware chats with persistent history and solid conversation management.
Speaks 90+ languages, making global rollouts straightforward.
Includes extras like lead capture (email collection) and smooth handoff to a human when needed.
Customization & Branding
Fully bespoke—design any UI you want and skin it to match your brand.
SciPhi focuses on the back end, so front-end look-and-feel is entirely up to you.
Default Gradio interface is pretty plain, with minimal theming.
For a branded UI you’ll tweak source code or build your own front end.
Fully white-labels the widget—colors, logos, icons, CSS, everything can match your brand.
White-label Options
Provides a no-code dashboard to set welcome messages, bot names, and visual themes.
Lets you shape the AI’s persona and tone using pre-prompts and system instructions.
Uses domain allowlisting to ensure the chatbot appears only on approved sites.
L L M Model Options
LLM-agnostic—GPT-4, Claude, Llama 2, you choose.
Pick, fine-tune, or swap models anytime to balance cost and performance
Model options.
Defaults to WizardVicuna-13B, but you can swap in any Hugging Face model if you have the GPUs.
Full control over model choice, though smaller open models won’t match GPT-4 for depth.
Taps into top models—OpenAI’s GPT-4, GPT-3.5 Turbo, and even Anthropic’s Claude for enterprise needs.
Automatically balances cost and performance by picking the right model for each request.
Model Selection Details
Uses proprietary prompt engineering and retrieval tweaks to return high-quality, citation-backed answers.
Handles all model management behind the scenes—no extra API keys or fine-tuning steps for you.
Developer Experience ( A P I & S D Ks)
REST API plus a Python client (R2RClient) handle ingest and query tasks
Python SDK.
Docs and GitHub repos offer deep dives and open-source starter code
SciPhi GitHub.
Interaction happens via Python scripts—there’s no formal REST API or SDK.
Integrations usually call those scripts as subprocesses or add your own wrapper.
Ships a well-documented REST API for creating agents, managing projects, ingesting data, and querying chat.
APIÂ Documentation
Offers open-source SDKs—like the Python customgpt-client—plus Postman collections to speed integration.
Open-Source SDK
Backs you up with cookbooks, code samples, and step-by-step guides for every skill level.
Integration & Workflow
Runs as a microservice—slot it into doc pipelines, CRMs, or any enterprise workflow.
Trigger ERP updates or support tickets straight from query escalations
Integration overview.
Run it locally: prep a GPU box, drop data, run prepare.py to embed, then chat.py for the Gradio UI.
Updating content means re-running scripts or using the new Knowledge tab; scaling is a manual process.
Gets you live fast with a low-code dashboard: create a project, add sources, and auto-index content in minutes.
Fits existing systems via API calls, webhooks, and Zapier—handy for automating CRM updates, email triggers, and more.
Auto-sync Feature
Slides into CI/CD pipelines so your knowledge base updates continuously without manual effort.
Performance & Accuracy
Hybrid search (dense + keyword) keeps retrieval fast and sharp.
Knowledge-graph boosts (HybridRAG) drive up to 150 % better accuracy
Benchmark details.
Sub-second latency—even at enterprise scale.
Open-source models run slower than managed clouds—expect a few to 10 + seconds per reply on a single GPU.
Accuracy is fine when the right doc is found, but smaller models can struggle on complex, multi-hop queries.
Delivers sub-second replies with an optimized pipeline—efficient vector search, smart chunking, and caching.
Independent tests rate median answer accuracy at 5/5—outpacing many alternatives.
Benchmark Results
Always cites sources so users can verify facts on the spot.
Maintains speed and accuracy even for massive knowledge bases with tens of millions of words.
We hope you found this comparison of SciPhi vs
SimplyRetrieve helpful.
SciPhi can power a deeply customized RAG stack, but expect significant engineering effort. If speed to launch trumps fine-grained control, you might look to a simpler managed service.
If local control and privacy outweigh convenience, SimplyRetrieve is a solid DIY route. Just be ready for the ongoing maintenance that comes with a self-hosted system.
Stay tuned for more updates!
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