In this comprehensive guide, we compare Pyx 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 Pyx and SimplyRetrieve!
Here are some unique insights on Pyx:
Pyx AI offers an internal knowledge search tool that employees can use right away—no APIs or code required. It’s great for quick wins inside the company but less flexible for external branding or deep integrations.
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
Pyx and SimplyRetrieve.
Detailed Feature Comparison
Features
Pyx
SimplyRetrieve
CustomGPTRECOMMENDED
Data Ingestion & Knowledge Sources
Focuses on unstructured data—you simply point it at your files and it indexes them right away.
Appvizer mention
Keeps connected file repositories in sync automatically, so any document changes show up almost instantly.
Works with common formats (PDF, DOCX, PPT, text, and more) and turns them into a chat-ready knowledge store.
Capterra listing
Doesn’t try to crawl whole websites or YouTube—the ingestion scope is intentionally narrower than CustomGPT’s.
Built for enterprise-scale volumes (exact limits not published) and aims for near-real-time indexing of large corporate data sets.
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
Comes with its own chat/search interface rather than a “deploy everywhere” model.
No built-in Slack bot, Zapier connector, or public API for external embeds.
Most users interact through Pyx’s web or desktop UI; synergy with other chat platforms is minimal for now.
Any deeper integration (say, Slack commands) would require custom dev work or future product updates.
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
Delivers conversational search over enterprise documents and keeps track of context for follow-up questions.
Appvizer reference
Geared toward internal knowledge management—features like lead capture or human handoff aren’t part of the roadmap.
Likely supports multiple languages to some extent, though it’s not a headline feature the way it is for CustomGPT.
Stores chat history inside the interface, but offers fewer business-oriented analytics than products with customer-facing use cases.
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
Designed as an internal tool with its own UI, so only minimal branding tweaks (logo/colors) are available.
No white-label or domain-embed options—Pyx lives as a standalone interface rather than a widget on your site.
The look and feel stay “Pyx AI” by design; public-facing brand alignment isn’t the goal here.
Emphasis is on security and user management over front-end theming.
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
Doesn’t expose model choice—Pyx likely runs GPT-3.5 or GPT-4 under the hood, but you can’t switch or fine-tune it.
No toggles for speed vs. accuracy; every query uses the same model configuration.
Focuses on its RAG engine with a single, undisclosed LLM—less flexible than tools that let you pick GPT-3.5 or GPT-4 explicitly.
No advanced re-ranking or multi-model routing options are mentioned.
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)
No open API or official SDKs—everything happens through the Pyx interface.
No open API
Embedding Pyx into other apps or calling it programmatically isn’t supported today.
Closed ecosystem: no GitHub examples or community plug-ins.
Great for teams wanting a turnkey tool, but it limits deep customization or dev-driven extensions.
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
Intended for employees to log in and query knowledge—no default embedding into external apps or websites.
No automation triggers or webhooks; usage is manual: ask a question, get an answer.
Scales to large data sets and supports role-based access, but lacks concepts like multi-bot setups.
User management note
For broader processes, each user still needs to open the Pyx app, limiting workflow integration.
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
Aims to serve accurate, real-time answers from internal documents—though public benchmark data is sparse.
Likely competitive with standard GPT-based RAG systems on relevance and hallucination control.
No detailed info on anti-hallucination tactics or turbo re-ranking like CustomGPT touts.
Auto-sync keeps documents fresh, so retrieval context is always current.
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 Pyx vs
SimplyRetrieve helpful.
If an easy internal search assistant is your goal, Pyx fits nicely. If you need full customization or external deployment, its closed approach could be limiting.
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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