Langchain vs SimplyRetrieve

Make an informed decision with our comprehensive comparison. Discover which RAG solution perfectly fits your needs.

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Langchain vs SimplyRetrieve Comparison
Priyansh Khodiyar's avatar
Priyansh KhodiyarDevRel at CustomGPT.ai

Fact checked and reviewed by Bill Cava

Published: 01.04.2025Updated: 25.04.2025

In this comprehensive guide, we compare Langchain 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 Langchain and SimplyRetrieve!

Here are some unique insights on Langchain:

LangChain is a developer library, not a SaaS. It lets you wire up LLMs, retrievers, and tools however you like. That freedom thrills coders but means you’re responsible for every piece of the puzzle.

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 Langchain and SimplyRetrieve.

Detailed Feature Comparison

Features
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Langchain
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SimplyRetrieve
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CustomGPTRECOMMENDED
Data Ingestion & Knowledge Sources
  • Takes a code-first approach: plug in document-loader modules for just about any file type—from PDFs with PyPDF to CSV, JSON, or HTML via Unstructured.
  • Lets developers craft custom ingestion and indexing pipelines, so niche or proprietary data sources are no problem.
  • 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 without a built-in web UI, so you’ll build your own front-end or pair it with something like Streamlit or React.
  • Includes libraries and examples for Slack (and other platforms), but you’ll handle the coding and config yourself.
  • 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, Zendesk, Confluence, YouTube, Sharepoint, 100+ more. 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.
  • Hosted CustomGPT.ai offers hosted MCP Server with support for Claude Web, Claude Desktop, Cursor, ChatGPT, Windsurf, Trae, etc. Read more here.
  • Supports OpenAI API Endpoint compatibility. Read more here.
Core Chatbot Features
  • Provides retrieval-augmented QA chains that blend LLM answers with data fetched from vector stores.
  • Supports multi-turn dialogue through configurable memory modules; you’ll add source citations manually if you need them.
  • Lets you build agents that call external APIs or tools for more advanced reasoning.
  • 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.
  • 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
  • Gives you the framework to design any UI you want, but offers no out-of-the-box white-label or branding features.
  • Total freedom to match corporate branding—just expect extra lift to build or integrate your own interface.
  • 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
  • Is completely model-agnostic—swap between OpenAI, Anthropic, Cohere, Hugging Face, and more through the same interface.
  • Easily adjust parameters and pick your embeddings or vector DB (FAISS, Pinecone, Weaviate) in just a few lines of code.
  • 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)
  • Comes as a Python or JavaScript library you import directly—there’s no hosted REST API by default.
  • Extensive docs, tutorials, and a huge community smooth the learning curve—but you do need programming skills. Reference
  • 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. API 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
  • Chain together LLM calls, retrievers, and prompt templates directly in code to create custom workflows.
  • Fits into CI/CD and event-driven architectures, though you’ll script the automation yourself.
  • 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
  • Accuracy hinges on your chosen LLM and prompt engineering—tune them well for top performance.
  • Response speed depends on the model and infra you choose; any extra optimization is up to your deployment.
  • 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.
Customization & Flexibility ( Behavior & Knowledge)
  • Gives you full control over prompts, retrieval settings, and integration logic—mix and match data sources on the fly.
  • Makes it possible to add custom behavioral rules and decision logic for highly tailored agents.
  • Lets you tweak everything—KnowledgeBase weight, retrieval params, system prompts—for deep control.
  • Encourages devs to swap embedding models or hack the pipeline code as needed.
  • Lets you add, remove, or tweak content on the fly—automatic re-indexing keeps everything current.
  • Shapes agent behavior through system prompts and sample Q&A, ensuring a consistent voice and focus. Learn How to Update Sources
  • Supports multiple agents per account, so different teams can have their own bots.
  • Balances hands-on control with smart defaults—no deep ML expertise required to get tailored behavior.
Pricing & Scalability
  • LangChain itself is open-source and free; costs come from the LLM APIs and infrastructure you run underneath.
  • Scaling is DIY: you manage hosting, vector-DB growth, and cost optimization—potentially very efficient once tuned.
  • Free, MIT-licensed open source—no fees, but you supply the GPUs or cloud servers.
  • Scaling means spinning up more hardware and managing it yourself.
  • Runs on straightforward subscriptions: Standard (~$99/mo), Premium (~$449/mo), and customizable Enterprise plans.
  • Gives generous limits—Standard covers up to 60 million words per bot, Premium up to 300 million—all at flat monthly rates. View Pricing
  • Handles scaling for you: the managed cloud infra auto-scales with demand, keeping things fast and available.
Security & Privacy
  • Security is fully in your hands—deploy on-prem or in your own cloud to meet whatever compliance rules you have.
  • No built-in security stack; you’ll add encryption, authentication, and compliance tooling yourself.
  • Entirely local: all docs and chat data stay on your own machine—great for sensitive use cases.
  • No built-in auth or enterprise security—lock things down in your own deployment setup.
  • Protects data in transit with SSL/TLS and at rest with 256-bit AES encryption.
  • Holds SOC 2 Type II certification and complies with GDPR, so your data stays isolated and private. Security Certifications
  • Offers fine-grained access controls—RBAC, two-factor auth, and SSO integration—so only the right people get in.
Observability & Monitoring
  • You’ll wire up observability in your app—LangChain doesn’t include a native analytics dashboard.
  • Tools like LangSmith give deep debugging and monitoring for tracing agent steps and LLM outputs. Reference
  • An “Analysis” tab shows which docs were pulled and how the query was built; logs print to the console.
  • No fancy dashboard—add your own logging or monitoring if you need broader stats.
  • Comes with a real-time analytics dashboard tracking query volumes, token usage, and indexing status.
  • Lets you export logs and metrics via API to plug into third-party monitoring or BI tools. Analytics API
  • Provides detailed insights for troubleshooting and ongoing optimization.
Support & Ecosystem
  • Backed by an active open-source community—docs, GitHub discussions, Discord, and Stack Overflow are all busy.
  • A wealth of community projects, plugins, and tutorials helps you find solutions fast. Reference
  • Open-source on GitHub; support is community-driven via issues and lightweight docs.
  • Smaller ecosystem: you’re free to fork or extend, but there’s no paid SLA or enterprise help desk.
  • Supplies rich docs, tutorials, cookbooks, and FAQs to get you started fast. Developer Docs
  • Offers quick email and in-app chat support—Premium and Enterprise plans add dedicated managers and faster SLAs. Enterprise Solutions
  • Benefits from an active user community plus integrations through Zapier and GitHub resources.
Additional Considerations
  • Total freedom to pick and swap models, embeddings, and vector stores—great for fast-evolving solutions.
  • Can power innovative, multi-step, tool-using agents, but reaching enterprise-grade polish takes serious engineering time.
  • Great for offline / on-prem labs where data never leaves the server—perfect for tinkering.
  • Takes more hands-on upkeep and won’t match proprietary giants in sheer capability out of the box.
  • Slashes engineering overhead with an all-in-one RAG platform—no in-house ML team required.
  • Gets you to value quickly: launch a functional AI assistant in minutes.
  • Stays current with ongoing GPT and retrieval improvements, so you’re always on the latest tech.
  • Balances top-tier accuracy with ease of use, perfect for customer-facing or internal knowledge projects.
No- Code Interface & Usability
  • Offers no native no-code interface—the framework is aimed squarely at developers.
  • Low-code wrappers (Streamlit, Gradio) exist in the community, but a full end-to-end UX still means custom development.
  • Basic Gradio UI is developer-focused; non-tech users might find the settings overwhelming.
  • No slick, no-code admin—if you need polish or branding, you’ll build your own front end.
  • Offers a wizard-style web dashboard so non-devs can upload content, brand the widget, and monitor performance.
  • Supports drag-and-drop uploads, visual theme editing, and in-browser chatbot testing. User Experience Review
  • Uses role-based access so business users and devs can collaborate smoothly.

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Final Thoughts

We hope you found this comparison of Langchain vs SimplyRetrieve helpful.

Choose LangChain when you want to craft something unique and don’t mind handling setup, hosting, and maintenance yourself.

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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Priyansh Khodiyar's avatar

Priyansh Khodiyar

DevRel at CustomGPT.ai. Passionate about AI and its applications. Here to help you navigate the world of AI tools and make informed decisions for your business.