What are the main differences between Guru and SciPhi R2R?

Guru excels in Permission-aware AI is unique differentiator - answers respect real-time access control and Enterprise-grade security: SOC 2, GDPR, zero LLM data retention, private models, scoring 86/100 in user ratings with N/A% accuracy. SciPhi R2R leads in State-of-the-art retrieval accuracy and Open-source with strong community with 89/100 overall rating and 92% accuracy. Key technical difference: Guru focuses on Permission-aware Knowledge Agents with real-time access control while SciPhi R2R emphasizes Multimodal ingestion (.pdf, .json, .png, .mp3, etc.). Pricing differs by $25/month.

Which is better for enterprises: Guru or SciPhi R2R?

Guru offers SOC 2 compliance for enterprise security. HIPAA compliance varies - contact vendors for details. For scalability, SciPhi R2R supports on-premise deployment for maximum control. SciPhi R2R leads with 89/100 enterprise readiness score (83/100 enterprise features).

How much does Guru cost vs SciPhi R2R?

Guru starts at $25/monthly (per-user model), while SciPhi R2R begins at contact sales/monthly (freemium model). Both offer free tiers to get started. Pricing is relatively comparable. See our detailed pricing breakdown for complete tier comparisons.

Can I migrate from Guru to SciPhi R2R?

Migration from Guru to SciPhi R2R typically requires API-based data export/import, which SciPhi R2R provides. SciPhi R2R provides comprehensive API access excellent documentation for the migration process. Estimated migration time: 1-2 days for cloud setup. Contact SciPhi R2R support for migration assistance and best practices.

What integrations do Guru and SciPhi R2R support?

Guru integrates with Native: Slack, Microsoft Teams, Salesforce, Zendesk, browser extension, Pre-built: ChatGPT, Claude, GitHub Copilot via MCP Server, Integration platforms: Zapier, Workato, Prismatic for 1,000+ apps, API access for custom integrations and embedded search, MCP (Model Context Protocol) Server for AI tool connectivity (8 integrations total). SciPhi R2R supports OpenAI, Anthropic Claude, Local LLMs, PostgreSQL, S3 storage (10 integrations available). Both offer REST APIs for custom integrations. SciPhi R2R provides 25% more integrations, with webhook support for real-time data sync.

What are the main differences between Guru and SciPhi?

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

Which is better for enterprises: Guru or SciPhi?

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

How much does Guru cost vs SciPhi?

Guru starts at custom pricing/month (subscription model), while SciPhi 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 Guru to SciPhi?

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

What integrations do Guru and SciPhi support?

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

Guru vs SciPhi

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

More about SciPhi More about Guru 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 Guru and SciPhi 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 Guru and SciPhi, 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 Guru if: you value permission-aware ai is unique differentiator - answers respect real-time access control
Choose SciPhi if: you value state-of-the-art retrieval accuracy

About Guru

Guru is ai-powered knowledge management and search platform. Enterprise AI knowledge platform with permission-aware Knowledge Agents that deliver trusted, cited answers from your company's verified knowledge base across all workflows. Founded in 2015, headquartered in Philadelphia, PA, USA, the platform has established itself as a reliable solution in the RAG space.

Overall Rating

86/100

Starting Price

$25/mo

About SciPhi

SciPhi is the most advanced ai retrieval system. R2R is a production-ready AI retrieval system supporting Retrieval-Augmented Generation with advanced features including multimodal ingestion, hybrid search, knowledge graphs, and a Deep Research API for multi-step reasoning across documents and the web. Founded in 2023, headquartered in San Francisco, CA, the platform has established itself as a reliable solution in the RAG space.

Overall Rating

89/100

Starting Price

Custom

Key Differences at a Glance

In terms of user ratings, both platforms score similarly in overall satisfaction. From a cost perspective, SciPhi offers more competitive entry pricing. The platforms also differ in their primary focus: Knowledge Management versus RAG Platform. 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

Guru	SciPhi	CustomGPTRECOMMENDED
Data Ingestion & Knowledge Sources
✅ Native Knowledge Base – Guru Cards with expert ownership and verification workflows Pre-Built Connectors – Google Drive, SharePoint, Confluence, Notion, Slack, Discord Automated Syncing – API/SDK, Zapier integrations for continuous updates Real-Time Indexing – Updates immediately reflected in AI responses Enterprise Scale – Handles millions of items across thousands of employees	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.	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
Integrations & Channels
✅ Native Workplace Apps – Slack, Microsoft Teams, browser extension ✅ AI Tool Integration – ChatGPT, Claude, GitHub Copilot via MCP Server Business Apps – Salesforce, Zendesk, Zapier (1,000+ apps) Developer Access – REST API, Python SDK, webhooks ⚠️ Internal Focus – Limited external channels like WhatsApp or Telegram	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 API snippet.	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
Core Chatbot Features
✅ Grounded Answers – All responses backed by verified knowledge with automatic citations ✅ Permission-Aware – Answers tailored to user's role and access permissions Custom Knowledge Agents – Specialized AI agents per team with role-specific insights Multi-Lingual – Content in all languages, translation to 50+ (UI English-only) Analytics Dashboard – Usage stats, deflection rates, time saved, knowledge gaps	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.	✅ #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 & Branding
Custom Agents – Unique name, avatar, scope per agent (IT, HR, Sales) Prompt Configuration – Custom instructions and system messages per agent No-Code Setup – Guided workflows via dashboard menu ⚠️ Limited White-Labeling – Guru branding present throughout platform	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.	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
L L M Model Options
⚠️ Abstracted Model – LLM selection handled internally, likely OpenAI GPT Private Models – Enterprise option for dedicated Azure OpenAI instance Zero Data Retention – Third-party LLM never stores customer data	LLM-agnostic—GPT-4, Claude, Llama 2, you choose. Pick, fine-tune, or swap models anytime to balance cost and performance Model options.	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
Developer Experience ( A P I & S D Ks)
REST API – Full coverage for Cards, Collections, AI queries ✅ MCP Server – Model Context Protocol for external AI access Python SDK & Webhooks – Official library and event subscriptions Automation Platforms – Pre-built Zapier, Workato connectors	REST API plus a Python client (`R2RClient`) handle ingest and query tasks Docs and GitHub repos offer deep dives and open-source starter code SciPhi GitHub.	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
Performance & Accuracy
✅ RAG Foundation – All answers grounded in verified company knowledge ✅ Automatic Citations – Every answer includes exact source references Multiple Retrieval Techniques – Several algorithms for optimal results Permission Filtering – Retrieval uses only authorized content Real-Time Accuracy – Updates immediately reflected in responses	Hybrid search (dense + keyword) keeps retrieval fast and sharp. Knowledge-graph boosts (HybridRAG) drive up to 150 % better accuracy Sub-second latency—even at enterprise scale.	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
Customization & Flexibility
Real-Time Updates – Edit Cards anytime, changes immediately available Agent Configuration – Custom prompts, intro messages per agent ⚠️ No Programmatic Personality – Dashboard-only config, no API	N/A	N/A
Pricing & Scalability
⚠️ Self-Serve Plan – $25/user/month (annual), $30/month (monthly), 10-user minimum Enterprise Plan – Custom pricing with volume discounts No Content Limits – Store thousands of Cards without fees Enterprise Scale – Supports thousands of employees in production	Free tier plus a $25/mo Dev tier for experiments. Enterprise plans with custom pricing and self-hosting for heavy traffic Pricing.	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 – Independently audited security controls ✅ GDPR Compliant – Data protection, EU residency options ✅ Zero LLM Data Retention – AI models never store customer data SAML SSO – Okta, Azure AD, Google Workspace integration Permission-Aware Security – AI respects real-time access controls	Customer data stays isolated in SciPhi Cloud; self-host for full control. Standard encryption in transit and at rest; tune self-hosted setups to meet any regulation.	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
Observability & Monitoring
AI Agent Center – Detailed logs of queries, answers, sources cited Analytics Dashboard – Usage stats, engagement, deflection metrics Trend Analysis – Identify frequently asked questions and knowledge gaps BI Integration – API access for Looker, Tableau	Dev dashboard shows real-time logs, latency, and retrieval quality Dashboard. Hook into Prometheus, Grafana, or other tools for deep monitoring.	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
Support & Ecosystem
Multi-Channel Support – Help Center, Community, live chat Enterprise Support – Dedicated CSM, priority support, SLAs Guru University – Training, workshops, certifications ✅ Exceptional Reputation – Praised in G2 for responsive support	Community help via Discord and GitHub; Enterprise customers get dedicated support Open-source core encourages community contributions and integrations.	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
No- Code Interface & Usability
Business User Focus – Designed for non-technical knowledge managers Intuitive Card Editor – Wiki-like interface similar to Notion Point-and-Click Integrations – OAuth connections via simple clicks No Developer Required – Business users maintain agents independently	No no-code UI—built for devs to wire into their own front ends. Dashboard is utilitarian: good for testing and monitoring, not for everyday business users.	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
Permission- Aware A I
✅ Real-Time Access Control – AI respects permissions from connected systems ✅ Role-Based Answers – Same question gets different answers per role Cross-System Permissions – Honors permissions from Drive, Notion, Salesforce ✅ Competitive Advantage – Most RAG platforms lack permission awareness	N/A	N/A
R A G-as-a- Service Assessment
Platform Type – TRUE RAG PLATFORM (Enterprise KM + AI) ✅ Key Differentiator – Permission-aware AI + verified knowledge Target Users – Enterprise teams (IT, HR, Sales), 1,000+ employees	Platform Type – HYBRID RAG-AS-A-SERVICE combining open-source R2R with managed SciPhi Cloud Core Mission – Bridge experimental RAG models to production-ready systems with deployment flexibility Developer Target – Built for OSS community, startups, enterprises emphasizing developer flexibility and control RAG Leadership – HybridRAG (150% accuracy), millions tokens/second, 40+ formats, sub-second latency ✅ Open-source R2R core on GitHub enables customization, portability, avoids vendor lock-in ⚠️ NO no-code features – No chat widgets, visual builders, pre-built integrations or dashboards	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
✅ Primary Advantage – Permission-aware AI with real-time access control ⚠️ Pricing Challenge – Per-user pricing expensive for large deployments ⚠️ Internal Focus – Optimized for internal knowledge, not external chatbots	Market position – Developer-first RAG infrastructure combining open-source flexibility with managed cloud service Target customers – Dev teams needing high-performance RAG, enterprises requiring millions tokens/second ingestion Key competitors – LangChain/LangSmith, Deepset/Haystack, Pinecone Assistant, custom RAG implementations Competitive advantages – HybridRAG (150% accuracy boost), async auto-scaling, 40+ formats, sub-second latency Pricing advantage – Free tier + $25/mo Dev plan; open-source foundation enables cost optimization Use case fit – Massive document volumes, advanced RAG needs, self-hosting control requirements	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
Abstracted Architecture – Likely OpenAI GPT (GPT-3.5/GPT-4) by default Private Options – Azure OpenAI in customer tenant for sovereignty Zero Data Retention – LLMs never store or train on data	LLM-Agnostic Architecture – GPT-4, GPT-3.5, Claude, Llama 2, and other open-source models Model Flexibility – Easy swapping to balance cost/performance without vendor lock-in Custom Support – Configure any LLM via API including fine-tuned or proprietary models Embedding Providers – Multiple embedding options for semantic search and vector generation ✅ Full control over temperature, max tokens, and generation parameters	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
✅ RAG Foundation – All answers grounded in verified knowledge with citations Permission Filtering – Prevents context contamination and leakage Real-Time Accuracy – Updates immediately reflected, no stale data	HybridRAG Technology – Vector search + knowledge graphs for 150% accuracy improvement Hybrid Search – Dense vector + keyword with reciprocal rank fusion Agentic RAG – Reasoning agent for autonomous research across documents and web Multimodal Ingestion – 40+ formats (PDFs, spreadsheets, audio) at massive scale ✅ Millions of tokens/second async auto-scaling ingestion throughput ✅ Sub-second latency even at enterprise scale with optimized operations	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 Internal Support – IT, HR, Sales, Support teams Knowledge Base Unification – Single source from SharePoint, Confluence, Notion Employee Onboarding – Role-appropriate info filtered by permission Regulatory Compliance – Financial, healthcare, legal with audit trails	Enterprise Knowledge – Process millions of documents with knowledge graph relationships Support Automation – RAG-powered support bots with accurate, grounded responses Research & Analysis – Agentic RAG for autonomous research across collections and web Compliance & Legal – Large document repositories with precise citation tracking Internal Docs – Developer-focused RAG for code, API references, technical knowledge Custom AI Apps – API-first architecture integrates into any application or workflow	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 – Third-party audited security controls GDPR Compliant – Data protection, EU residency options Zero LLM Data Retention – Contractual guarantee with providers SAML SSO & SCIM – Okta, Azure AD, Google Workspace integration	Data Isolation – Single-tenant architecture with isolated customer data in SciPhi Cloud Self-Hosting Option – On-premise deployment for complete data control in regulated industries Encryption Standards – TLS in transit, AES-256 at rest encryption Access Controls – Document-level granular permissions with role-based access control (RBAC) ✅ Open-source R2R core enables security audits and compliance validation ✅ Self-hosted deployments tunable for HIPAA, SOC 2, and other regulations	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
Self-Serve Plan – $25/user/month (annual), 10-user minimum Enterprise Plan – Custom pricing with volume discounts ⚠️ Seat-Based Model – Expensive for large deployments vs query-based	Free Tier – Generous no-credit-card tier for experimentation and development Developer Plan – $25/month for individual developers and small projects Enterprise Plans – Custom pricing based on scale, features, and support Self-Hosting – Open-source R2R available free (infrastructure costs only) ✅ Flat subscription pricing without per-query or per-document charges ✅ Managed cloud handles infrastructure, deployment, scaling, updates, maintenance	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
Multi-Channel Support – Help Center, Community, live chat Enterprise Support – Dedicated CSM, priority support, SLAs Guru University – Training, workshops, certifications	Comprehensive Docs – Detailed docs at r2r-docs.sciphi.ai covering all features and endpoints GitHub Repository – Active open-source development at github.com/SciPhi-AI/R2R with code examples Community Support – Discord community and GitHub issues for peer support Enterprise Support – Dedicated channels for enterprise customers with SLAs ✅ Python client (R2RClient) with extensive examples and starter code ✅ Developer dashboard with real-time logs, latency, and retrieval quality metrics	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
Additional Considerations
⚠️ Content Maintenance Required – Value depends on disciplined refreshing ⚠️ Per-User Pricing – Expensive for 1,000+ users vs alternatives Best For – Internal KM with verified workflows culture	Advanced extras like GraphRAG and agentic flows push beyond basic Q&A Great fit for enterprises needing deeply customized, fully integrated AI solutions.	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
Limitations & Considerations
⚠️ Per-User Pricing – Expensive for 1,000+ users vs query-based ⚠️ Internal Focus – Not optimized for external chatbots ⚠️ Limited White-Labeling – Guru branding present in app ⚠️ Model Abstraction – No LLM selection reduces flexibility	⚠️ Developer-Focused – Requires technical expertise to build and wire custom front ends ⚠️ Infrastructure Requirements – Self-hosting needs GPU infrastructure and DevOps expertise ⚠️ Integration Effort – API-first design means building your own chat UI ⚠️ Learning Curve – Advanced features like knowledge graphs require RAG concept understanding ⚠️ Community Support Limits – Open-source support relies on community unless enterprise plan	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
Customization & Flexibility ( Behavior & Knowledge)
N/A	Add new sources, tweak retrieval, mix collections—everything’s programmable. Chain API calls, re-rank docs, or build full agentic flows	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
Core Agent Features
N/A	Agentic RAG – Reasoning agent for autonomous research across documents/web with multi-step problem solving Advanced Toolset – Semantic search, metadata search, document retrieval, web search, web scraping capabilities Multi-Turn Context – Stateful dialogues maintaining conversation history via conversation_id for follow-ups Citation Transparency – Detailed responses with source citations for fact-checking and verification ⚠️ No Pre-Built UI – API-first platform requires custom front-end development ⚠️ No Lead Analytics – Lead capture and dashboards must be implemented at application layer	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

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Final Thoughts

Final Verdict: Guru vs SciPhi

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

When to Choose Guru

You value permission-aware ai is unique differentiator - answers respect real-time access control
Enterprise-grade security: SOC 2, GDPR, zero LLM data retention, private models
Verified knowledge base with expert verification workflows ensures accuracy

Best For: Permission-aware AI is unique differentiator - answers respect real-time access control

When to Choose SciPhi

You value state-of-the-art retrieval accuracy
Open-source with strong community
Production-ready with proven scalability

Best For: State-of-the-art retrieval accuracy

Migration & Switching Considerations

Switching between Guru and SciPhi 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

Guru starts at $25/month, while SciPhi 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 Guru and SciPhi 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: February 23, 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.

Guru vs SciPhi