SciPhi vs SearchUnify

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

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 SciPhi and SearchUnify 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 SciPhi and SearchUnify, 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 SciPhi if: you value state-of-the-art retrieval accuracy
  • Choose SearchUnify if: you value g2 leader for 21 consecutive quarters (5+ years) in enterprise search - exceptional market validation vs newer rag startups

About SciPhi

SciPhi Landing Page Screenshot

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

About SearchUnify

SearchUnify Landing Page Screenshot

SearchUnify is ai-powered unified enterprise search and knowledge management. Enterprise cognitive search platform with proprietary Federated RAG (FRAG™) architecture, 100+ pre-built connectors, and mature Salesforce integration. G2 Leader for 21 consecutive quarters (5+ years). Parent company Grazitti Interactive (founded 2008) maintains SOC 2 Type 2 + ISO 27001 + HIPAA compliance. BYOLLM flexibility supports OpenAI, Azure, Google Gemini, Hugging Face, custom models. Critical gaps: NO WhatsApp/Telegram messaging, NO public pricing (AWS Marketplace: $0.01-$0.025/request), NO Zapier integration. Enterprise search heritage vs RAG-first positioning. Founded in 2008 (Grazitti), SearchUnify product launched ~2012, headquartered in Panchkula, India / San Jose, CA, USA, the platform has established itself as a reliable solution in the RAG space.

Overall Rating
84/100
Starting Price
Custom

Key Differences at a Glance

In terms of user ratings, both platforms score similarly in overall satisfaction. From a cost perspective, pricing is comparable. The platforms also differ in their primary focus: RAG Platform versus Enterprise Search. 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

logo of sciphi
SciPhi
logo of searchunify
SearchUnify
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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.
  • 35+ content parsers – PDF, DOC, DOCX, PPT, CSV, TXT, XSL with 12MB size limit per document
  • 100+ pre-built connectors – Salesforce, ServiceNow, Zendesk, SharePoint, Confluence, Google Drive
  • YouTube indexing – Channel/playlist/video-level with timestamped transcript search
  • Auto-sync – 15-minute to manual intervals, webhook-based real-time for Box, Docebo
  • ⚠️ No Notion integration – Notable gap vs competitors supporting Notion knowledge bases
  • ⚠️ 12MB document limit – May constrain large PDF processing
  • 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
  • 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.
  • Native search clients – Salesforce Service Console, ServiceNow, Zendesk, Khoros, Slack
  • Salesforce Summit Partner – Highest tier with AppExchange, native UX integration
  • RESTful API – OAuth 2.0, Swagger docs, three official SDKs (JS, Python, Java)
  • ⚠️ No consumer messaging – NO WhatsApp, Telegram, Facebook Messenger
  • ⚠️ No Zapier – Significant gap for no-code automation vs 7,000+ app competitors
  • 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
  • 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.
N/A
  • ✅ #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
  • 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.
  • Theme editor – Colors, fonts, icons, messaging without code
  • NLP Manager – Synonyms, acronyms, keywords per language
  • Visual search tuning – Boost/downgrade rankings via admin UI
  • Temperature controls – Per-persona, use case, audience type
  • 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
  • LLM-agnostic—GPT-4, Claude, Llama 2, you choose.
  • Pick, fine-tune, or swap models anytime to balance cost and performance Model options.
  • BYOLLM architecture – Avoid vendor lock-in with flexible model selection
  • Claude via Bedrock – 14-day trial, OpenAI, Azure OpenAI, Google Gemini
  • Hugging Face support – Open-source models for custom deployments
  • Multiple connections – Connect providers simultaneously with failover
  • ⚠️ No auto routing – Manual configuration vs query complexity-based routing
  • 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 plus a Python client (R2RClient) handle ingest and query tasks
  • Docs and GitHub repos offer deep dives and open-source starter code SciPhi GitHub.
  • Three official SDKs – JavaScript (su-sdk), Python (searchunify), Java (Maven)
  • MCP support – su-mcp library for Claude Desktop and LLM tooling
  • RESTful API v2 – Swagger docs, OAuth 2.0 (4-hour access, 14-day refresh tokens)
  • ⚠️ Rate limits unclear – Requires community documentation access
  • ⚠️ No API versioning policy – Potential breaking change risk
  • 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
  • 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.
  • 120-second analytics – Near real-time dashboard refresh
  • FRAG™ mitigation – 3-layer architecture reduces hallucinations
  • Customer results – Accela 99.7% cost savings, Cornerstone 98% self-service
  • YouTube timestamps – Transcript search returns exact audio segments
  • 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 ( Behavior & Knowledge)
  • Add new sources, tweak retrieval, mix collections—everything’s programmable.
  • Chain API calls, re-rank docs, or build full agentic flows
N/A
  • 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
Pricing & Scalability
  • Free tier plus a $25/mo Dev tier for experiments.
  • Enterprise plans with custom pricing and self-hosting for heavy traffic Pricing.
N/A
  • 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
  • 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.
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
Observability & Monitoring
  • Dev dashboard shows real-time logs, latency, and retrieval quality Dashboard.
  • Hook into Prometheus, Grafana, or other tools for deep monitoring.
  • 30+ pre-built metrics – Search performance, conversion tracking, content gaps
  • Actionable Insights – AI-generated plain-English recommendations
  • SUVA metrics – Deflection rate, handover, CSAT, LLM token usage
  • Admin activity logs – 30-day retention with CSV export
  • 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
  • Community help via Discord and GitHub; Enterprise customers get dedicated support
  • Open-source core encourages community contributions and integrations.
  • SearchUnify Academy – Free training with certifications
  • 97-98% G2 satisfaction – "Ease of Doing Business With" rating
  • G2 Leader – 21 consecutive quarters in Enterprise Search
  • Enterprise support – Phone, email, chat with dedicated account managers
  • 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
Core Agent Features
  • 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
  • SUVA Virtual Assistant – "World's First Federated RAG Chatbot" analyzing 20+ attributes
  • 35+ languages – Native Arabic, German, French, Mandarin with extended CSV config
  • Human handoff – Escalation to Salesforce, Zendesk, Khoros with full context
  • SearchUnifyGPT™ – LLM answers with inline citations above traditional search
  • Up to 5 agents – Per instance deployable across portals
  • 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
  • Advanced extras like GraphRAG and agentic flows push beyond basic Q&A
  • Great fit for enterprises needing deeply customized, fully integrated AI solutions.
  • ✅ 100+ connectors – Reduced integration effort, 7-14 day deployment
  • ✅ FRAG™ architecture – Enterprise hallucination mitigation
  • ✅ Salesforce Summit – Deepest native integration available
  • ⚠️ Cloud-only – No on-premise/air-gapped option
  • ⚠️ No public pricing – Requires sales engagement
  • ⚠️ No consumer messaging – WhatsApp, Telegram, Zapier absent
  • 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
No- Code Interface & Usability
  • 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.
  • 97-98% G2 usability – Consistently high "Ease of Use" ratings
  • Visual configuration – OAuth flows, content sources via admin UI
  • Drag-and-drop – Salesforce Console search client components
  • SUVA Agent Builder – Visual config for up to 5 agents per instance
  • 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
Competitive Positioning
  • 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
  • G2 + IDC + Forrester – Leader 21 quarters, MarketScape Major Player
  • 100+ connectors – Reduced integration effort vs custom connector platforms
  • Salesforce Summit – Native UX integration vs API-only competitors
  • ⚠️ Cloud-only – No on-premise/air-gapped deployment
  • ⚠️ No consumer messaging – Enterprise support channels only
  • 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
  • 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
  • BYOLLM – Claude (Bedrock), OpenAI, Azure, Gemini, Hugging Face
  • Multiple connections – Simultaneous providers with activation toggles
  • Temperature controls – Per-persona creativity adjustment
  • Failover mechanisms – Automatic when primary LLMs unavailable
  • 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
  • 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
  • FRAG™ 3-layer – Federation + Retrieval + Augmented Generation
  • Hybrid search – Full-text + vector + ML re-ranking combined
  • Multi-repository – Docs, forums, LMS, CRM unified retrieval
  • Hallucination mitigation – Sensitive data removal before LLM transmission
  • 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 – 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
  • Enterprise support – SUVA deflects tickets with federated knowledge
  • Salesforce enhancement – Native Service Console and Communities integration
  • Multi-system unification – 100+ sources consolidated (CRM, LMS, SharePoint)
  • Training/LMS search – YouTube transcripts + Docebo + documentation unified
  • 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
  • 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 1/2/3 Type II – ISO 27001, ISO 27701, HIPAA, GDPR compliant
  • Single-tenant – Customer data isolation, no cross-tenant leakage
  • AES-256 + TLS 1.3 – Encryption at rest and in transit
  • SSO integration – SAML 2.0 with Okta, Azure AD, OneLogin, Google
  • FRAG security – Sensitive data removal before LLM transmission
  • 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
  • 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
  • ⚠️ No public pricing – Requires enterprise sales engagement
  • AWS Marketplace – 100K searches: $0.025/req, 200K: $0.015, 300K: $0.01
  • Unlimited connectors – Flat subscription, no per-connector fees
  • 7-14 day deployment – Using pre-built connectors
  • ⚠️ Annual escalation – Reviews note "guaranteed price increase every year"
  • 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
  • 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
N/A
  • 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
R A G-as-a- Service Assessment
  • 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 – ENTERPRISE COGNITIVE SEARCH with RAG, not pure RaaS
  • 5+ years leadership – G2 Leader 21 quarters with RAG as enhancement
  • FRAG™ differentiator – Proprietary federated architecture for enterprise
  • Target users – Large enterprises with 100+ fragmented knowledge sources
  • ⚠️ Not for developers – Not lightweight API-first RAG for SMBs
  • 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
Limitations & Considerations
  • ⚠️ 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
  • ⚠️ No public pricing – Requires sales engagement, annual escalation clauses
  • ⚠️ No consumer messaging – NO WhatsApp, Telegram, Messenger native
  • ⚠️ No Zapier – Major gap for no-code automation workflows
  • ⚠️ Cloud-only – No on-premise/air-gapped for regulated industries
  • ⚠️ 12MB document limit – May constrain large PDF processing
  • Best for – Salesforce-centric enterprises; not API-first developers
  • 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
F R A G™ Architecture ( Core Differentiator)
N/A
  • Federated RAG – 3-layer framework for hallucination mitigation in enterprise retrieval
  • Federation Layer – 360-degree context across 100+ connected sources simultaneously
  • Retrieval Layer – Keyword matching + semantic similarity + vector search combined
  • ✅ Multi-repository context – Docs, forums, LMS, CRM, tickets unified for comprehensive answers
N/A

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Final Thoughts

Final Verdict: SciPhi vs SearchUnify

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

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

When to Choose SearchUnify

  • You value g2 leader for 21 consecutive quarters (5+ years) in enterprise search - exceptional market validation vs newer rag startups
  • Proprietary FRAG™ architecture specifically designed for hallucination mitigation with 3-layer federation, retrieval, augmented generation
  • 100+ pre-built connectors dramatically reduce integration effort - Google Drive, Salesforce, ServiceNow, Zendesk, Slack, MS Teams, YouTube, Adobe AEM

Best For: G2 Leader for 21 consecutive quarters (5+ years) in Enterprise Search - exceptional market validation vs newer RAG startups

Migration & Switching Considerations

Switching between SciPhi and SearchUnify 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

SciPhi starts at custom pricing, while SearchUnify 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

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

For most organizations, the decision between SciPhi and SearchUnify 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 24, 2026 | This comparison is regularly reviewed and updated to reflect the latest platform capabilities, pricing, and user feedback.

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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.

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