What are the main differences between Pyx AI and SearchUnify?

Pyx AI excels in Very quick setup (30-60 minutes) and No manual data imports required, scoring 83/100 in user ratings with 85% accuracy. SearchUnify leads in G2 Leader for 21 consecutive quarters (5+ years) in Enterprise Search - exceptional market validation vs newer RAG startups and Proprietary FRAG™ architecture specifically designed for hallucination mitigation with 3-layer federation, retrieval, augmented generation with 84/100 overall rating and N/A% accuracy. Key technical difference: Pyx AI focuses on Conversational search interface while SearchUnify emphasizes Federated RAG (FRAG™): Proprietary 3-layer architecture (Federation, Retrieval, Augmented Generation) for hallucination mitigation across 100+ enterprise sources. Pricing differs by $30/month.

Which is better for enterprises: Pyx AI or SearchUnify?

SearchUnify offers SOC 2 compliance for enterprise security. HIPAA compliance is available in SearchUnify. For scalability, Pyx AI supports on-premise deployment for maximum control. SearchUnify leads with 84/100 enterprise readiness score.

How much does Pyx AI cost vs SearchUnify?

Pyx AI starts at $30/monthly (freemium model), while SearchUnify begins at contact sales/month (enterprise model). Pyx AI offers a free tier, and free trials are available. Pricing is relatively comparable. See our detailed pricing breakdown for complete tier comparisons.

Can I migrate from Pyx AI to SearchUnify?

Migration from Pyx AI to SearchUnify typically requires API-based data export/import, which SearchUnify provides. SearchUnify provides comprehensive API access good documentation for the migration process. Estimated migration time: 1-2 weeks for full deployment. Contact SearchUnify support for migration assistance and best practices.

What integrations do Pyx AI and SearchUnify support?

Pyx AI integrates with SharePoint, Google Drive, Dropbox, OneDrive, Local file systems (7 integrations total). SearchUnify supports Native search clients: Salesforce Service Console/Communities, ServiceNow, Zendesk Support/Help Center, Khoros Aurora/Classic, Slack, Marketplace presence: Salesforce AppExchange (Summit Partner), ServiceNow Store, Microsoft AppSource, Embedding: JavaScript widget, custom React/Handlebars components (Khoros), native widgets (Salesforce/ServiceNow consoles), SearchUnifyGPT™ Answer Box: LLM answers above traditional search with inline citations, Webhooks: Real-time sync and SUVA integration with external applications (8 integrations available). SearchUnify offers API capabilities. SearchUnify provides 14% more integrations.

What are the main differences between Pyx and SearchUnify?

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

Which is better for enterprises: Pyx or SearchUnify?

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

How much does Pyx cost vs SearchUnify?

Pyx starts at custom pricing/month (subscription model), while SearchUnify 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 Pyx to SearchUnify?

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

What integrations do Pyx and SearchUnify support?

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

Pyx vs SearchUnify

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

More about SearchUnify More about Pyx 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 Pyx 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 Pyx 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 Pyx if: you value very quick setup (30-60 minutes)
Choose SearchUnify if: you value g2 leader for 21 consecutive quarters (5+ years) in enterprise search - exceptional market validation vs newer rag startups

About Pyx

Pyx is find. don't search.. Pyx AI is an enterprise conversational search tool that leverages Retrieval-Augmented Generation (RAG) to deliver real-time answers from company data. It continuously synchronizes with data sources and enables natural language queries across unstructured documents without keywords or pre-sorting. Founded in 2022, headquartered in Europe, the platform has established itself as a reliable solution in the RAG space.

Overall Rating

83/100

Starting Price

$30/mo

About SearchUnify

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, SearchUnify offers more competitive entry pricing. The platforms also differ in their primary focus: AI Search 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

Pyx	SearchUnify	CustomGPTRECOMMENDED
Data Ingestion & Knowledge Sources
✅ Auto-Indexing – Points at files, indexes unstructured data automatically without manual setup ✅ Auto-Sync – Connected repositories sync automatically, document changes reflected almost instantly File Formats – Supports PDF, DOCX, PPT, TXT and common enterprise formats ⚠️ Limited Scope – No website crawling or YouTube ingestion, narrower than CustomGPT Enterprise Scale – Handles large corporate data sets, exact limits not published	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
⚠️ Standalone Only – Own chat/search interface, not a "deploy everywhere" platform ⚠️ No External Channels – No Slack bot, Zapier connector, or public API Web/Desktop UI – Users interact through Pyx's interface, minimal third-party chat synergy Custom Integration – Deeper integrations require custom dev work or future updates	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
Conversational Search – Context-aware Q&A over enterprise documents with follow-up questions ⚠️ Internal Focus – Designed for knowledge management, no lead capture or human handoff Multi-Language – Likely supports multiple languages, though not a headline feature ⚠️ Basic Analytics – Stores chat history, fewer business insights than customer-facing tools	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
⚠️ Minimal Branding – Logo/color tweaks only, designed as internal tool not white-label ⚠️ No Embedding – Standalone interface, no domain-embed or widget options available Pyx UI Only – Look stays "Pyx AI" by design, public branding not supported Security Focus – Emphasis on user management and access controls over theming	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
⚠️ Undisclosed Model – Likely GPT-3.5/GPT-4 but exact model not publicly documented ⚠️ No Model Selection – Cannot switch LLMs or configure speed vs accuracy tradeoffs ⚠️ Single Configuration – Every query uses same model, no toggles or fine-tuning Closed Architecture – Model details, context window, capabilities hidden from users intentionally	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)
⚠️ No API – No open API or SDKs, everything through Pyx interface ⚠️ No Embedding – Cannot integrate into other apps or call programmatically Closed Ecosystem – No GitHub examples, community plug-ins, or extensibility options Turnkey Only – Great for ready-made tool, limits deep customization or extensions	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
Real-Time Answers – Serves accurate responses from internal documents, sparse public benchmarks Auto-Sync Freshness – Connected repositories keep retrieval context always current automatically ⚠️ Limited Transparency – No anti-hallucination metrics or advanced re-ranking details published Competitive RAG – Likely comparable to standard GPT-based systems on relevance control	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)
✅ Auto-Sync Updates – Knowledge base updated without manual uploads or scheduling ⚠️ No Persona Controls – AI voice stays neutral, no tone or behavior customization ✅ Access Controls – Strong role-based permissions, admins set document visibility per user Closed Environment – Great for content updates, limited for AI behavior or deployment	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
Seat-Based Pricing – ~$30 per user per month, predictable monthly costs ✅ Cost-Effective Small Teams – Affordable for teams under 50 users ⚠️ Large Team Costs – 100 users = $3,000/month, can scale expensively Unlimited Content – Document/token limits not published, gated only by user seats Free Trial + Enterprise – Hands-on trial available, custom pricing for large deployments	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
✅ GDPR Compliance – Germany-based, implicit EU data protection and regional sovereignty ✅ Enterprise Privacy – Data isolated per customer, encrypted in transit and rest ✅ No Model Training – Customer data not used for external LLM training ✅ Role-Based Access – Built-in controls, admins set document visibility per role ⚠️ Limited Certifications – On-prem or SOC 2/ISO 27001/HIPAA not publicly documented	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
Basic Stats – User activity, query counts, top-referenced documents for admins ⚠️ No Deep Analytics – No conversation analytics dashboards or real-time logging Adoption Tracking – Useful for usage monitoring, lighter insights than full suites Set-and-Forget – Minimal monitoring overhead, contact support for issues	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
✅ Direct Support – Email, phone, chat with hands-on onboarding approach ⚠️ No Open Community – Closed solution, no plug-ins or user-built extensions Internal Roadmap – Product updates from Pyx only, no community marketplace Quick Setup Focus – Emphasizes minimal admin overhead for internal knowledge search	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
Additional Considerations
✅ No-Fuss Internal Search – Employees use without coding, simple deployment for teams ⚠️ Not Public-Facing – Not ideal for customer chatbots or developer-heavy customization Siloed Environment – Single AI search environment, not broad extensible platform Simpler Scope – Less flexible than CustomGPT, but faster setup for internal use	✅ 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
✅ Straightforward UI – Users log in, ask questions, get answers without coding ✅ No-Code Admin – Admins connect data sources, Pyx indexes automatically Minimal Customization – UI stays consistent and uncluttered by design Internal Q&A Hub – Perfect for employee use, not external embedding or branding	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 – Turnkey internal knowledge search (Germany), not embeddable chatbot platform Target Customers – Small-mid European teams needing GDPR compliance and simple deployment Key Competitors – Glean, Guru, Notion AI; not customer-facing chatbots like CustomGPT ✅ Advantages – Simple scope, auto-sync, GDPR compliance, ~$30/user/month predictable pricing ⚠️ Use Case Fit – Perfect for <50 user teams, not API integrations or public chatbots	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
⚠️ Undisclosed LLM – Likely GPT-3.5/GPT-4 but model details not publicly documented ⚠️ No Model Selection – Cannot switch LLMs or choose speed vs accuracy configurations ⚠️ Opaque Architecture – Context window size and capabilities not exposed to users Simplicity Focus – Hides technical complexity, users ask questions and get answers ⚠️ No Fine-Tuning – Cannot customize model on domain data for specialized responses	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
Conversational RAG – Context-aware search over enterprise documents with follow-up support ✅ Auto-Sync – Repositories sync automatically, changes reflected almost instantly Document Formats – PDF, DOCX, PPT, TXT and common enterprise formats supported ⚠️ No Advanced Controls – Chunking, embedding models, similarity thresholds not exposed ⚠️ Limited Transparency – No citation metrics or anti-hallucination details published Closed System – Optimized for internal Q&A, limited visibility into retrieval architecture	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
✅ Internal Knowledge Search – Employees asking questions about company documents and policies ✅ Team Onboarding – New hires finding information without bothering colleagues ✅ Policy Lookup – HR, compliance, operational procedure retrieval for staff ✅ Small European Teams – GDPR-compliant internal search with EU data residency ⚠️ NOT SUITABLE FOR – Public chatbots, customer support, API integrations, multi-channel deployment	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
✅ GDPR Compliance – Germany-based with implicit EU data protection compliance ✅ German Data Residency – EU storage location for regional data sovereignty requirements ✅ Enterprise Privacy – Customer data isolated, encrypted in transit and at rest ✅ Role-Based Access – Built-in controls, admins set document visibility per user ⚠️ Limited Certifications – SOC 2, ISO 27001, HIPAA not publicly documented	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
Seat-Based Pricing – ~$30 per user per month ✅ Small Team Value – Affordable for teams under 50 users, predictable costs ⚠️ Scalability Cost – 100 users = $3,000/month, expensive for large organizations Unlimited Content – No published document limits, gated only by user seats Free Trial + Enterprise – Evaluation available, custom pricing for volume discounts	⚠️ 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
✅ Direct Support – Email, phone, chat with hands-on onboarding approach ✅ Quick Deployment – Minimal admin overhead, connect sources and start asking questions ⚠️ No Open Community – Closed solution, no plug-ins or user extensions ⚠️ No Developer Docs – No API documentation or programmatic access guides Internal Roadmap – Updates from Pyx only, no user-contributed features	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
Limitations & Considerations
⚠️ No Public API – Cannot embed or call programmatically, standalone UI only ⚠️ No Messaging Integrations – No Slack, Teams, WhatsApp or chat platform connectors ⚠️ Limited Branding – Minimal customization, not white-label solution for public deployment ⚠️ No Advanced Controls – Cannot configure RAG parameters, model selection, retrieval strategies ⚠️ Seat-Based Scaling – Expensive for large orgs vs usage-based pricing models ✅ Best For – Small European teams (<50 users) prioritizing simplicity and GDPR over flexibility	⚠️ 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
Core Agent Features
⚠️ NO Agent Capabilities – No autonomous agents, tool calling, or multi-agent orchestration Conversational Search Only – Context-aware dialogue for Q&A, not agentic or autonomous behavior Basic RAG Architecture – Standard retrieval without function calling, tool use, or workflows ⚠️ No External Actions – Cannot invoke APIs, execute code, query databases, or interact externally Internal Knowledge Focus – Employee Q&A about documents, not task automation or workflows	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
R A G-as-a- Service Assessment
⚠️ NOT TRUE RAG-AS-A-SERVICE – Standalone internal app, not API-accessible RAG platform Turnkey Application – Self-contained Q&A tool vs developer-accessible RAG infrastructure ⚠️ No API Access – No REST API, SDKs, programmatic access unlike CustomGPT/Vectara Closed Application – Web/desktop interface only, cannot build custom applications on top SaaS vs RaaS – Software-as-a-Service (standalone app) NOT Retrieval-as-a-Service (API infrastructure) Best Comparison Category – Internal search tools (Glean, Guru), not developer RAG platforms	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
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: Pyx vs SearchUnify

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

When to Choose Pyx

You value very quick setup (30-60 minutes)
No manual data imports required
Excellent ease of use with conversational interface

Best For: Very quick setup (30-60 minutes)

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 Pyx 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

Pyx starts at $30/month, 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

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 Pyx 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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The most accurate RAG-as-a-Service API. Deliver production-ready reliable RAG applications faster. Benchmarked #1 in accuracy and hallucinations for fully managed RAG-as-a-Service API.

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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.

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