What are the main differences between Glean and LangChain?

Glean excels in Permissions-aware AI is genuinely differentiated - real-time enforcement across 100+ datasources addresses critical enterprise concern and Strong developer experience - comprehensive APIs, 4-language SDKs (Python, Java, Go, TypeScript), LangChain integration, scoring 96/100 in user ratings with 90% accuracy. LangChain leads in Most popular LLM framework (72M+ downloads/month) and Extensive integration ecosystem (600+) with 87/100 overall rating and 86% accuracy. Key technical difference: Glean focuses on Permissions-aware AI with real-time access control enforcement while LangChain emphasizes Modular LLM framework. Pricing differs by $50/month.

Which is better for enterprises: Glean or LangChain?

Glean offers SOC 2 compliance for enterprise security. HIPAA compliance is available in Glean. For scalability, both offer cloud-based deployment options. Glean leads with 96/100 enterprise readiness score (98/100 enterprise features).

How much does Glean cost vs LangChain?

Glean starts at $50/monthly (enterprise model), while LangChain begins at contact sales/monthly (freemium model). LangChain provides a free tier. Pricing is relatively comparable. See our detailed pricing breakdown for complete tier comparisons.

Can I migrate from LangChain to Glean?

Migration from LangChain to Glean typically requires API-based data export/import, which Glean provides. Glean provides comprehensive API access excellent documentation for the migration process. Estimated migration time: 1-2 days for cloud setup. Contact Glean support for migration assistance and best practices.

What integrations do Glean and LangChain support?

Glean integrates with Cloud Storage: Google Drive, SharePoint, OneDrive, Dropbox, Box, Communication: Slack (full bot support), Microsoft Teams, Gmail, Outlook, Zoom, Collaboration: Confluence, Notion, Jira, GitHub, GitLab, Miro, CRM/Support: Salesforce, ServiceNow, Zendesk, Identity: Okta, Microsoft Entra ID, Google Workspace, OneLogin (8 integrations total). LangChain supports OpenAI, Anthropic, Google, AWS Bedrock, Azure AI (11 integrations available). Both offer REST APIs for custom integrations. LangChain provides 38% more integrations, with webhook support for real-time data sync.

What are the main differences between Glean and Langchain?

Glean offers strong capabilities, scoring 0/100 in user ratings. Langchain provides unique strengths with 0/100 overall rating. Key technical difference: Glean focuses on advanced features while Langchain emphasizes specialized capabilities.

Which is better for enterprises: Glean or Langchain?

Both platforms provide enterprise-grade security. HIPAA compliance varies - contact vendors for details. For scalability, both offer cloud-based deployment options. Langchain leads with strong/100 enterprise readiness score.

How much does Glean cost vs Langchain?

Glean starts at custom pricing/month (subscription model), while Langchain begins at contact sales/month (subscription model). Both require paid plans. Pricing is relatively comparable. See our detailed pricing breakdown for complete tier comparisons.

Can I migrate from Glean to Langchain?

Migration from Glean to Langchain typically requires manual data transfer since API access may be limited. Langchain offers standard documentation for the migration process. Estimated migration time: 1-2 days for cloud setup. Contact Langchain support for migration assistance and best practices.

What integrations do Glean and Langchain support?

Glean integrates with (multiple platforms). Langchain supports (various tools). API availability varies by plan. Integration coverage is comparable.

Glean vs Langchain

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

More about Langchain More about Glean Get Started Today

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 Glean and Langchain across various parameters including features, pricing, performance, and customer support to help you make the best decision for your business needs.

Overview

When choosing between Glean and Langchain, understanding their unique strengths and architectural differences is crucial for making an informed decision. Both platforms serve the RAG (Retrieval-Augmented Generation) space but cater to different use cases and organizational needs.

Quick Decision Guide

Choose Glean if: you value permissions-aware ai is genuinely differentiated - real-time enforcement across 100+ datasources addresses critical enterprise concern
Choose Langchain if: you value most popular llm framework (72m+ downloads/month)

About Glean

Glean is enterprise work ai with permissions-aware rag across 100+ apps. Glean is a premium enterprise RAG platform with permissions-aware AI as its core differentiator. Founded by ex-Google Search engineers, Glean achieved $100M ARR in three years and a $7.2B valuation (2025). It connects 100+ enterprise apps with real-time access controls, supports 15+ LLMs, and offers comprehensive APIs with 4-language SDKs. Trade-offs: enterprise-only sales (~$50/user/month, ~$60K minimum), no consumer messaging channels, and premium positioning over plug-and-play simplicity. Founded in 2019, headquartered in Palo Alto, CA, the platform has established itself as a reliable solution in the RAG space.

Overall Rating

96/100

Starting Price

$50/mo

About Langchain

Langchain is the most popular open-source framework for building llm applications. LangChain is a comprehensive AI development framework that simplifies building applications with LLMs through modular components, chains, and agent orchestration, offering both open-source tools and commercial platforms. Founded in 2022, headquartered in San Francisco, CA, the platform has established itself as a reliable solution in the RAG space.

Overall Rating

87/100

Starting Price

Custom

Key Differences at a Glance

In terms of user ratings, Glean in overall satisfaction. From a cost perspective, Langchain offers more competitive entry pricing. The platforms also differ in their primary focus: Enterprise RAG versus AI Framework. These differences make each platform better suited for specific use cases and organizational requirements.

⚠️ What This Comparison Covers

We'll analyze features, pricing, performance benchmarks, security compliance, integration capabilities, and real-world use cases to help you determine which platform best fits your organization's needs. All data is independently verified from official documentation and third-party review platforms.

Detailed Feature Comparison

Glean	Langchain	CustomGPTRECOMMENDED
Data Ingestion & Knowledge Sources
✅ 100+ native connectors – Cloud storage, CRM, collaboration platforms plus Indexing API File formats – PDFs, Word, HTML, spreadsheets, structured data Real-time sync – Content within minutes, permission changes immediate ⚠️ Initial indexing – Few days depending on volume Scale – 10K-100K users, hundreds of millions of documents	100+ document loaders – PDF, CSV, JSON, HTML, Markdown, Notion, Confluence, GitHub via code Custom pipelines – Build proprietary ingestion for any data source with full control ⚠️ Code-first only – No UI for data upload; requires Python/JS development	1,400+ file formats – PDF, DOCX, Excel, PowerPoint, Markdown, HTML + auto-extraction from ZIP/RAR/7Z archives Website crawling – Sitemap indexing with configurable depth for help docs, FAQs, and public content Multimedia transcription – AI Vision, OCR, YouTube/Vimeo/podcast speech-to-text built-in Cloud integrations – Google Drive, SharePoint, OneDrive, Dropbox, Notion with auto-sync Knowledge platforms – Zendesk, Freshdesk, HubSpot, Confluence, Shopify connectors Massive scale – 60M words (Standard) / 300M words (Premium) per bot with no performance degradation
L L M Model Options
✅ 15+ LLMs supported – GPT-4, Gemini 1.5 Pro, Claude 3 Sonnet Per-step model selection – Different LLMs for each workflow step Temperature controls – Factual, balanced, or creative output settings BYOK support – Glean Universal Key or Customer Key options Automatic routing – Zero data retention, optimizes top models per query	Model-agnostic – OpenAI, Anthropic, Cohere, Hugging Face, local models Any vector DB – FAISS, Pinecone, Weaviate, Chroma, Qdrant supported Self-hosted option – Run Llama, Mistral locally for data privacy Easy switching – Change providers with minimal code changes	GPT-5.1 models – Latest thinking models (Optimal & Smart variants) GPT-4 series – GPT-4, GPT-4 Turbo, GPT-4o available Claude 4.5 – Anthropic's Opus available for Enterprise Auto model routing – Balances cost/performance automatically Zero API key management – All models managed behind the scenes
Performance & Accuracy
✅ 74% human-agreement rate – 25% precision increases 141% ROI over 3 years – Forrester Total Economic Impact 110 hours saved per employee annually – Productivity gains Hallucination prevention – RAG grounding, permissions, citations	You control quality – Accuracy depends on LLM and prompt tuning DIY optimization – Response speed depends on your infrastructure ⚠️ No built-in benchmarks – Test and optimize yourself	Sub-second responses – Optimized RAG with vector search and multi-layer caching Benchmark-proven – 13% higher accuracy, 34% faster than OpenAI Assistants API Anti-hallucination tech – Responses grounded only in your provided content OpenGraph citations – Rich visual cards with titles, descriptions, images 99.9% uptime – Auto-scaling infrastructure handles traffic spikes
Developer Experience ( A P I & S D Ks)
✅ Client & Indexing APIs – Search, Chat, Agents, Documents, Governance Official SDKs – Python, Java, Go, TypeScript with async support Web SDK – Embeddable chat, search, autocomplete, recommendations components Framework integrations – LangChain, CrewAI, OpenAI Assistants, MCP Server Authentication – OAuth 2.0, user-scoped tokens, impersonation support	Python & JS libraries – Import directly, no hosted REST API Largest LLM community – 100K+ GitHub stars, 50K+ Discord members Extensive docs – Tutorials, API reference, community plugins ⚠️ Programming required – No no-code or low-code options	REST API – Full-featured for agents, projects, data ingestion, chat queries Python SDK – Open-source `customgpt-client` with full API coverage Postman collections – Pre-built requests for rapid prototyping Webhooks – Real-time event notifications for conversations and leads OpenAI compatible – Use existing OpenAI SDK code with minimal changes
Integrations & Channels
Slack & Teams – Official apps, Gleanbot auto-responses, Real-Time Search API Browser extensions – Chrome (300K+ users), Firefox, Safari, Edge ⚠️ No WhatsApp/Telegram – Designed for internal enterprise use only SSO protocols – OIDC, SAML 2.0 with Okta, Microsoft Entra	No built-in UI – Build your own with Streamlit, React, or custom frontend Slack/Discord examples – Community libraries available, but you handle coding ⚠️ DIY deployment – All integrations require custom development	Website embedding – Lightweight JS widget or iframe with customizable positioning CMS plugins – WordPress, WIX, Webflow, Framer, SquareSpace native support 5,000+ app ecosystem – Zapier connects CRMs, marketing, e-commerce tools MCP Server – Integrate with Claude Desktop, Cursor, ChatGPT, Windsurf OpenAI SDK compatible – Drop-in replacement for OpenAI API endpoints LiveChat + Slack – Native chat widgets with human handoff capabilities
Customization & Branding
UI customization – Custom logos, color schemes, background images Custom subdomains – your-company.glean.com Chat widget styling – CSS positioning, width/height, custom containers ⚠️ Limited white-labeling – Glean branding may remain visible	Total flexibility – Design any UI you want from scratch ⚠️ No white-label features – No out-of-box branding tools ⚠️ Extra development – Custom frontend required for any UI	Full white-labeling included – Colors, logos, CSS, custom domains at no extra cost 2-minute setup – No-code wizard with drag-and-drop interface Persona customization – Control AI personality, tone, response style via pre-prompts Visual theme editor – Real-time preview of branding changes Domain allowlisting – Restrict embedding to approved sites only
Core R A G Features
✅ Hybrid search – Semantic (vector-based) + lexical (keyword) approaches Knowledge Graph Framework – Proprietary anchors across enterprise data LLM Control Layer – Optimizes outputs with context-aware query rewriting Grounded answers – Source citations with every response	N/A	N/A
Permissions- Aware A I ( Core Differentiator)
✅ Real-time access control – Across all 100+ datasources Identity crawling – Users, groups, memberships, permission models Connector-level mirroring – Respects native permissions (Salesforce, GDrive) Zero-trust architecture – Users only see authorized content	N/A	N/A
Multi- Language & Localization
Full support – English, German, Japanese (semantic, assistant, UI) Partial support – French, Spanish 20+ languages – Early access or keyword search	N/A	N/A
Observability & Monitoring
Insights Dashboard – DAU/WAU/MAU, Search Session Satisfaction metrics Usage metrics – Searches and chats per user per week 270-day data retention – Department-level filtering Audit logging – User activity, access patterns, SIEM export	LangSmith – Debugging and tracing for agent workflows ⚠️ No native dashboard – Requires LangSmith subscription or DIY	Real-time dashboard – Query volumes, token usage, response times Customer Intelligence – User behavior patterns, popular queries, knowledge gaps Conversation analytics – Full transcripts, resolution rates, common questions Export capabilities – API export to BI tools and data warehouses
Pricing & Scalability
⚠️ No public pricing – Enterprise sales only Estimated cost – ~$45-50+ per user/month Minimum ACV – ~$60K (approximately 100 users minimum) No free trial – Paid POCs up to $70K Annual contracts – Per-seat model, 7-12% renewal increases, FlexCredits for premium	Framework: Free – MIT license, no usage limits DIY scaling – Manage hosting, vector DB growth, optimization ⚠️ Total cost – LLM APIs + infra + dev time often exceeds managed platforms	Standard: $99/mo – 60M words, 10 bots Premium: $449/mo – 300M words, 100 bots Auto-scaling – Managed cloud scales with demand Flat rates – No per-query charges
Security & Privacy
✅ SOC 2 Type II, ISO 27001, HIPAA, GDPR ⚠️ No FedRAMP – Not for US federal government AES-256 at rest, TLS 1.2+ in transit Single-tenant – Isolated per customer, Cloud-Prem option	N/A	SOC 2 Type II + GDPR – Third-party audited compliance Encryption – 256-bit AES at rest, SSL/TLS in transit Access controls – RBAC, 2FA, SSO, domain allowlisting Data isolation – Never trains on your data
No- Code Interface & Usability
✅ Natural language configuration – Describe goals in plain language Visual builder – Drag-and-drop workflow creation AI-assisted creation – Auto-generates draft agents 30+ prebuilt agents – Sales, engineering, IT, HR	No no-code interface – Developer-only framework Community wrappers – Streamlit, Gradio for basic UIs ⚠️ Custom dev required – Full end-to-end UX needs coding	2-minute deployment – Fastest time-to-value in the industry Wizard interface – Step-by-step with visual previews Drag-and-drop – Upload files, paste URLs, connect cloud storage In-browser testing – Test before deploying to production Zero learning curve – Productive on day one
Support & Ecosystem
Standard support – 24x5 via portal, email, Slack Connect Premium support – 24x7 critical issues with additional fee ✅ Excellent documentation – developers.glean.com with OpenAPI specs GitHub repositories – SDK examples and sample projects	Active community – Discord, GitHub, Stack Overflow support 700+ integrations – Community-contributed plugins and tools ⚠️ No enterprise SLA – Community support only for free tier	Comprehensive docs – Tutorials, cookbooks, API references Email + in-app support – Under 24hr response time Premium support – Dedicated account managers for Premium/Enterprise Open-source SDK – Python SDK, Postman, GitHub examples 5,000+ Zapier apps – CRMs, e-commerce, marketing integrations
Conversation & Agent Features
Conversation history – Thread tracking in Slack, History tab Version control – All agent versions auto-saved ⚠️ No lead capture – Designed for internal enterprise use	N/A	N/A
Deployment Options
Cloud (SaaS) – Standard Glean infrastructure deployment Cloud-Prem – Customer-hosted in AWS or GCP Single-tenant architecture – Isolated per customer	N/A	N/A
R A G-as-a- Service Assessment
✅ TRUE RAG PLATFORM – API-first with comprehensive tools Data flexibility – 100+ connectors, Indexing API Best for – Large enterprises requiring permissions-aware RAG	Platform type – FRAMEWORK, NOT RAG-AS-A-SERVICE DIY architecture – Build entire pipeline from scratch with code No managed infrastructure – You host vector DB, LLM, servers Best for: Teams building custom RAG with full control Alternative: For managed RaaS, use CustomGPT, Vectara, or Azure AI	Platform type – TRUE RAG-AS-A-SERVICE with managed infrastructure API-first – REST API, Python SDK, OpenAI compatibility, MCP Server No-code option – 2-minute wizard deployment for non-developers Hybrid positioning – Serves both dev teams (APIs) and business users (no-code) Enterprise ready – SOC 2 Type II, GDPR, WCAG 2.0, flat-rate pricing
Competitive Positioning
✅ Unique strength – Real-time permissions-aware AI across 100+ datasources Proven ROI – 141% ROI, 110 hours/employee saved ⚠️ Pricing barrier – ~$50/user/month, ~$60K minimum	Market position – Leading open-source LLM framework, largest developer community Target users – Developers/ML engineers wanting maximum flexibility vs CustomGPT – Weeks of coding vs 2-minute deployment; full control vs managed service vs Haystack/LlamaIndex – Larger community, more integrations NOT for: Non-technical users, rapid deployment, teams without ML expertise	Market position – Leading RAG platform balancing enterprise accuracy with no-code usability. Trusted by 6,000+ orgs including Adobe, MIT, Dropbox. Key differentiators – #1 benchmarked accuracy • 1,400+ formats • Full white-labeling included • Flat-rate pricing vs OpenAI – 10% lower hallucination, 13% higher accuracy, 34% faster vs Botsonic/Chatbase – More file formats, source citations, no hidden costs vs LangChain – Production-ready in 2 min vs weeks of development
A I Models
✅ 15+ LLMs – GPT-4, Gemini 1.5 Pro, Claude 3 with per-step selection Temperature controls – Factual, balanced, or creative output BYOK support – Customer Key for data sovereignty	OpenAI – GPT-4, GPT-4 Turbo, GPT-3.5 with full control Anthropic – Claude 3 Opus/Sonnet with 200K context Hugging Face – 100K+ models including Llama, Mistral, Falcon Self-hosted – Ollama, GPT4All for complete privacy	OpenAI – GPT-5.1 (Optimal/Smart), GPT-4 series Anthropic – Claude 4.5 Opus/Sonnet (Enterprise) Auto-routing – Intelligent model selection for cost/performance Managed – No API keys or fine-tuning required
R A G Capabilities
✅ Hybrid search – Semantic + lexical for accuracy Knowledge Graph Framework – Proprietary anchors across data 74% human-agreement – 25% precision increases	Full RAG toolkit – Loaders, splitters, embeddings, retrievers, chains 100+ vector stores – Pinecone, Chroma, Weaviate, FAISS, Milvus Hybrid search – Combine vector + keyword (BM25) retrieval Reranking – Cohere Rerank, cross-encoder models supported	GPT-4 + RAG – Outperforms OpenAI in independent benchmarks Anti-hallucination – Responses grounded in your content only Automatic citations – Clickable source links in every response Sub-second latency – Optimized vector search and caching Scale to 300M words – No performance degradation at scale
Use Cases
Enterprise knowledge – Unified search across 100+ datasources Permissions-aware – Healthcare, finance, legal hierarchies AI agents – 30+ prebuilt for sales, engineering, IT	Custom RAG apps – Enterprise knowledge bases with full control Multi-step agents – Research, analysis, automation workflows Code assistance – Generation, review, documentation tools ⚠️ Weeks to deploy – Unlike 2-minute turnkey platforms	Customer support – 24/7 AI handling common queries with citations Internal knowledge – HR policies, onboarding, technical docs Sales enablement – Product info, lead qualification, education Documentation – Help centers, FAQs with auto-crawling E-commerce – Product recommendations, order assistance
Security & Compliance
✅ SOC 2 Type II, ISO 27001, HIPAA, GDPR ⚠️ NO FedRAMP – Not for US federal government Single-tenant – Isolated per customer, Cloud-Prem option	On-premise deployment – Run in your VPC for data sovereignty Self-hosted models – Llama, Mistral via Ollama for full privacy ⚠️ DIY security – No built-in encryption, auth, or compliance ⚠️ No SLA – Open-source means no uptime guarantees	SOC 2 Type II + GDPR – Regular third-party audits, full EU compliance 256-bit AES encryption – Data at rest; SSL/TLS in transit SSO + 2FA + RBAC – Enterprise access controls with role-based permissions Data isolation – Never trains on customer data Domain allowlisting – Restrict chatbot to approved domains
Pricing & Plans
⚠️ No public pricing – Enterprise sales only ~$45-50+/user/month – Estimated cost from reports ~$60K minimum ACV – Approximately 100 users minimum	Framework: FREE – MIT license, unlimited commercial use LangSmith Dev: Free – 5K traces/month for debugging LangSmith Plus: $39/seat/mo – Team collaboration, 10K traces ⚠️ Hidden costs – LLM APIs + vector DB + hosting + dev time	Standard: $99/mo – 10 chatbots, 60M words, 5K items/bot Premium: $449/mo – 100 chatbots, 300M words, 20K items/bot Enterprise: Custom – SSO, dedicated support, custom SLAs 7-day free trial – Full Standard access, no charges Flat-rate pricing – No per-query charges, no hidden costs
Support & Documentation
24x5 standard support – Portal, email, Slack Connect ✅ Excellent documentation – developers.glean.com with OpenAPI Official SDKs – Python, Java, Go, TypeScript	Official docs – python.langchain.com with tutorials, API reference Community – 50K+ Discord, 7K+ GitHub discussions ⚠️ Doc quality mixed – Some gaps, rapidly changing APIs	Documentation hub – Docs, tutorials, API references Support channels – Email, in-app chat, dedicated managers (Premium+) Open-source – Python SDK, Postman, GitHub examples Community – User community + 5,000 Zapier integrations
Limitations & Considerations
⚠️ High cost barrier – ~$50/user/month, ~$60K minimum ⚠️ NO FedRAMP – Not for US federal government ⚠️ No consumer channels – No WhatsApp, Telegram Complex implementation – Indexing takes days	⚠️ Programming mandatory – Python/JS skills required ⚠️ Weeks-months to production – Not rapid deployment ⚠️ DIY everything – Security, UI, monitoring, compliance ⚠️ Breaking changes – Frequent API updates require maintenance ⚠️ Hidden infrastructure costs – LLM + DB + hosting adds up Ideal for: Teams with ML engineers wanting maximum control	Managed service – Less control over RAG pipeline vs build-your-own Model selection – OpenAI + Anthropic only; no Cohere, AI21, open-source Real-time data – Requires re-indexing; not ideal for live inventory/prices Enterprise features – Custom SSO only on Enterprise plan
Core Agent Features
✅ Autonomous AI agents – Understand tasks, execute autonomously Natural language builder – Describe goals, auto-designs workflows 100+ native actions – Slack, Teams, Salesforce, Jira, GitHub	LangGraph – Low-level agentic framework launched 2024 Tool calling – Agents autonomously invoke APIs and functions Multi-step workflows – Average 7.7 steps per trace in 2024 Custom architectures – Build specialized agent systems	Custom AI Agents – Autonomous GPT-4/Claude agents for business tasks Multi-Agent Systems – Specialized agents for support, sales, knowledge Memory & Context – Persistent conversation history across sessions Tool Integration – Webhooks + 5,000 Zapier apps for automation Continuous Learning – Auto re-indexing without manual retraining
Additional Considerations
⚠️ Cannot create content directly – Focuses on search/retrieval Large organization focus – May be overkill for smaller teams Training investment – Upskilling employees needed	Significant engineering investment – Weeks to months for production Hidden costs – Infrastructure often exceeds managed platform fees Breaking changes – Frequent updates require code maintenance Ideal for: Teams with dedicated ML engineers	Time-to-value – 2-minute deployment vs weeks with DIY Always current – Auto-updates to latest GPT models Proven scale – 6,000+ organizations, millions of queries Multi-LLM – OpenAI + Claude reduces vendor lock-in
Core Chatbot Features
Glean Chat interface – Natural conversations with company knowledge Multi-turn conversations – Context awareness across turns Streaming responses – Real-time with source citations	RAG chains – Retrieval-augmented QA combining LLMs with vector stores Multi-turn memory – Configurable conversation memory modules Tool-calling agents – External API and tool execution capabilities ⚠️ No built-in citations – Manual implementation required for source links	✅ #1 accuracy – Median 5/5 in independent benchmarks, 10% lower hallucination than OpenAI ✅ Source citations – Every response includes clickable links to original documents ✅ 93% resolution rate – Handles queries autonomously, reducing human workload ✅ 92 languages – Native multilingual support without per-language config ✅ Lead capture – Built-in email collection, custom forms, real-time notifications ✅ Human handoff – Escalation with full conversation context preserved
Customization & Flexibility ( Behavior & Knowledge)
Natural language config – Build agents without technical expertise Visual builder – Drag-and-drop workflow creation 30+ templates – Sales, engineering, IT, HR	Full control – Prompts, retrieval, chains, agents customizable Custom logic – Add any behavioral rules or decision patterns Mix data sources – Combine multiple knowledge bases on the fly	Live content updates – Add/remove content with automatic re-indexing System prompts – Shape agent behavior and voice through instructions Multi-agent support – Different bots for different teams Smart defaults – No ML expertise required for custom behavior

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Final Thoughts

Final Verdict: Glean vs Langchain

After analyzing features, pricing, performance, and user feedback, both Glean and Langchain are capable platforms that serve different market segments and use cases effectively.

When to Choose Glean

You value permissions-aware ai is genuinely differentiated - real-time enforcement across 100+ datasources addresses critical enterprise concern
Strong developer experience - comprehensive APIs, 4-language SDKs (Python, Java, Go, TypeScript), LangChain integration
Model flexibility without vendor lock-in - 15+ LLMs with per-step selection and bring-your-own-key option

Best For: Permissions-aware AI is genuinely differentiated - real-time enforcement across 100+ datasources addresses critical enterprise concern

When to Choose Langchain

You value most popular llm framework (72m+ downloads/month)
Extensive integration ecosystem (600+)
Strong developer community

Best For: Most popular LLM framework (72M+ downloads/month)

Migration & Switching Considerations

Switching between Glean and Langchain requires careful planning. Consider data export capabilities, API compatibility, and integration complexity. Both platforms offer migration support, but expect 2-4 weeks for complete transition including testing and team training.

Pricing Comparison Summary

Glean starts at $50/month, while Langchain begins at custom pricing. Total cost of ownership should factor in implementation time, training requirements, API usage fees, and ongoing support. Enterprise deployments typically see annual costs ranging from $10,000 to $500,000+ depending on scale and requirements.

Our Recommendation Process

Start with a free trial - Both platforms offer trial periods to test with your actual data
Define success metrics - Response accuracy, latency, user satisfaction, cost per query
Test with real use cases - Don't rely on generic demos; use your production data
Evaluate total cost - Factor in implementation time, training, and ongoing maintenance
Check vendor stability - Review roadmap transparency, update frequency, and support quality

For most organizations, the decision between Glean and Langchain comes down to specific requirements rather than overall superiority. Evaluate both platforms with your actual data during trial periods, focusing on accuracy, latency, ease of integration, and total cost of ownership.

📚 Next Steps

Ready to make your decision? We recommend starting with a hands-on evaluation of both platforms using your specific use case and data.

• Review: Check the detailed feature comparison table above
• Test: Sign up for free trials and test with real queries
• Calculate: Estimate your monthly costs based on expected usage
• Decide: Choose the platform that best aligns with your requirements

Last updated: January 20, 2026 | This comparison is regularly reviewed and updated to reflect the latest platform capabilities, pricing, and user feedback.

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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.

Glean vs Langchain