What are the main differences between Deviniti and SimplyRetrieve?

Deviniti excels in Strong compliance and security focus and Self-hosted solutions for data privacy, scoring 77/100 in user ratings with 81% accuracy. SimplyRetrieve leads in Completely free and open source and Strong privacy focus - fully localized with 82/100 overall rating and 86% accuracy. Key technical difference: Deviniti focuses on Custom AI agent development while SimplyRetrieve emphasizes Retrieval-Centric Generation (RCG).

Which is better for enterprises: Deviniti or SimplyRetrieve?

Both platforms provide enterprise-grade security. HIPAA compliance is available in Deviniti. For scalability, both offer cloud-based deployment options. SimplyRetrieve leads with 82/100 enterprise readiness score (70/100 enterprise features).

How much does Deviniti cost vs SimplyRetrieve?

Deviniti starts at custom pricing/custom (enterprise model), while SimplyRetrieve begins at contact sales/forever (open-source model). SimplyRetrieve provides a free tier. Pricing is relatively comparable. See our detailed pricing breakdown for complete tier comparisons.

Can I migrate from Deviniti to SimplyRetrieve?

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

What integrations do Deviniti and SimplyRetrieve support?

Deviniti integrates with Atlassian suite, Enterprise systems, Custom APIs, Banking systems, Legal platforms (7 integrations total). SimplyRetrieve supports Hugging Face models, Gradio, PyTorch, FAISS, Various open-source LLMs (6 integrations available). SimplyRetrieve offers API capabilities. Deviniti offers 17% more integrations, with webhook support for real-time data sync.

What are the main differences between Deviniti and SimplyRetrieve?

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

Which is better for enterprises: Deviniti or SimplyRetrieve?

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

How much does Deviniti cost vs SimplyRetrieve?

Deviniti starts at custom pricing/month (subscription model), while SimplyRetrieve 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 Deviniti to SimplyRetrieve?

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

What integrations do Deviniti and SimplyRetrieve support?

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

Deviniti vs SimplyRetrieve

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

More about SimplyRetrieve More about Deviniti 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 Deviniti and SimplyRetrieve 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 Deviniti and SimplyRetrieve, 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 Deviniti if: you value strong compliance and security focus
Choose SimplyRetrieve if: you value completely free and open source

About Deviniti

Deviniti is self-hosted genai solutions for compliance-critical industries. Deviniti is an AI development company specializing in secure, self-hosted AI agents and LLM solutions for highly regulated industries like finance, healthcare, and legal, with expertise in RAG architecture and custom AI development. Founded in 2010, headquartered in Kraków, Poland, the platform has established itself as a reliable solution in the RAG space.

Overall Rating

77/100

Starting Price

Custom

About SimplyRetrieve

SimplyRetrieve is lightweight retrieval-centric generative ai platform. SimplyRetrieve is an open-source tool providing a fully localized, lightweight, and user-friendly GUI and API platform for Retrieval-Centric Generation (RCG). It emphasizes privacy and can run on a single GPU while maintaining clear separation between LLM context interpretation and knowledge memorization. Founded in 2019, headquartered in Tokyo, Japan, the platform has established itself as a reliable solution in the RAG space.

Overall Rating

82/100

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: AI Development 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

Deviniti	SimplyRetrieve	CustomGPTRECOMMENDED
Data Ingestion & Knowledge Sources
Custom pipelines – Ingest any source: docs, APIs, databases, proprietary systems Case study Format support – PDF, DOCX, and uncommon formats as needed Scalable infrastructure – Automated pipelines for huge datasets with fresh indexing Learn more ⚠️ Custom build required – No pre-built connectors or templates	File-Based Workflow – Drop PDFs, DOCX, PPTX, HTML into folder and embed via script GUI Knowledge Editor – Add documents on-the-fly through basic interface Manual Processing – ⚠️ No web crawler or automatic refresh capabilities Local Storage – ✅ All data stays on your machine for air-gapped deployments	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
Multi-channel deployment – Web, mobile, Slack, Teams, or legacy apps Custom APIs – Webhooks for CRMs, ERPs, ITSM with dev work Integration approach ✅ Tailored to stack – Fits exact enterprise architecture requirements ⚠️ Dev effort needed – Each integration requires custom development sprint	Local Gradio GUI – Python scripts for queries with no pre-built channels No Native Integrations – ⚠️ No Slack, Teams, or website widgets out-of-box Custom Wrappers Required – Build your own connectors to forward messages	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
Domain-tuned AI – Multi-turn memory, context, any language, local LLMs Workflow automation – Lead capture, human handoff, IT tickets Case study ✅ Exact specifications – Built precisely to your requirements	Open-Source RAG Bot – Runs on local LLMs with streaming responses Single-Turn Q&A – ⚠️ Limited multi-turn conversation and long-term memory Retrieval Tuning Module – Transparency layer showing answer construction process Basic Interactions – No lead capture or human handoff features	✅ #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 – UI, tone, flows match brand perfectly Custom approach Domain-specific dialogs – Custom styling and terminology for your industry ⚠️ Changes require dev – Updates need development effort, not self-service	Plain Gradio Interface – Minimal theming with developer-focused design Source Code Customization – Tweak code or build custom front-end for branding	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
Model-agnostic – GPT-4, Claude, Llama 2, Falcon, any model Services Fine-tuning – Train on proprietary data for insider terminology Local deployment – On-prem hosting for complete data sovereignty ⚠️ Model swaps – Require new build/deploy cycle	WizardVicuna-13B Default – Instruction-tuned open-source model included Hugging Face Compatible – Swap any model with sufficient GPU resources Full Local Control – ✅ No external APIs or cloud dependencies Model Limitations – ⚠️ Smaller models won't match GPT-4 depth	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)
Project-specific API – JSON over HTTP tailored to endpoints Example Custom docs – Documentation and samples from Deviniti engineers ✅ Direct support – Access to dev team, not generic docs ⚠️ No public SDK – Everything custom-built for your project	Python Script Interface – No formal REST API or SDK Subprocess Integration – Call scripts directly or build custom wrapper Open Source Access – ✅ Full code access for modification	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
Best-practice retrieval – Multi-index, tuned prompts for precision Approach Hallucination reduction – Fine-tune on your data for accuracy ⚠️ Ongoing refinement – Perfecting accuracy needs iterative tweaks	Slower Inference – ⚠️ 3-10+ seconds per reply on single GPU Decent Accuracy – Good when relevant docs found, struggles with complexity FAISS Vector Search – Fast retrieval using Facebook's library	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)
Total control – Add sources, tweak tone, inject APIs Details Unlimited flexibility – Dream it, Deviniti builds it ⚠️ Dev sprints – Updates usually require quick development work	Deep Parameter Control – Tweak retrieval params, system prompts, knowledge weighting Embedding Model Swap – Replace multilingual-e5-base with alternatives Pipeline Modification – ✅ Full source access for custom logic	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
Project-based – $50K-$500K+ initial, optional maintenance Portfolio Scale to millions – Infrastructure handles huge query volumes ✅ No subscription fees – Own outright without recurring costs ⚠️ High upfront – Much costlier than $29-$999/mo SaaS solutions	MIT Licensed – ✅ Completely free with no subscription fees Infrastructure Costs – Pay only for GPU hardware or cloud servers Manual Scaling – ⚠️ Spin up and manage your own hardware	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
On-prem/private cloud – Full data control and compliance Security Strong encryption – AES-256 at rest, TLS 1.3 in transit Security stack integration – Hooks into SIEM, monitoring, access controls ✅ Data sovereignty – No third-party sharing or cloud vendor dependencies	100% Local Execution – ✅ Perfect for sensitive data and air-gapped environments No External Transmission – All processing stays on-premises DIY Security – ⚠️ No built-in auth, you implement access controls	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
Custom monitoring – CloudWatch, Prometheus integration Info Admin dashboards – Real-time analytics, alerts, SIEM feeds ✅ Enterprise tools – Integrates with existing monitoring infrastructure	Analysis Tab – Shows retrieved docs and query construction process Console Logging – Basic logs printed to terminal No Dashboard – ⚠️ Add your own monitoring for stats	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
White-glove support – Direct dev team access, kickoff through post-launch Services Stack-specific docs – Training and documentation tailored to your infrastructure ✅ 200+ clients – Proven track record with Fortune 500 enterprises	Community-Driven – GitHub issues and lightweight documentation Research Foundation – Academic paper (arXiv 2308.03983) on RCG approach No Paid Support – ⚠️ No SLA or enterprise help desk	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
Hybrid agents – Complex transactional tasks beyond Q&A Custom governance End-to-end ownership – Own and evolve solution as AI advances ✅ Future-proof – Complete control over technology roadmap	N/A	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 tools – IT or admin panels handle configuration User experience – End users chat; tech team manages tweaks	N/A	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 – Custom AI agency (200+ clients), enterprise RAG specialist Target customers – Large enterprises needing custom solutions, legacy system integration Key competitors – Azumo, internal AI teams, Contextual.ai, AI consultancies Advantages – Proven track record, model-agnostic, on-prem deployment, solution ownership Pricing advantage – Higher upfront, no subscriptions; best for unique needs Use case fit – Legacy systems, domain-tuned models, hybrid agents, data sovereignty	Market Position – MIT open-source local RAG for on-premises deployment Target Customers – Developers experimenting locally, strict data isolation orgs Key Competitors – LangChain, LlamaIndex, PrivateGPT, LocalGPT Advantages – ✅ Free MIT license, 100% local, full model control Best For – Offline environments, GPU infrastructure teams, zero cloud costs	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
Model-agnostic – GPT-4, Claude, Llama 2, Falcon, Cohere, custom models Fine-tuning – Proprietary data training for domain-specific terminology Local LLMs – On-prem hosting for sovereignty and offline operation Multiple models – Different models for different use cases ⚠️ Model swaps – Require build/deploy cycle for changes	WizardVicuna-13B – Default uncensored instruction-tuned model Any Hugging Face Model – Llama 2, Falcon, Mistral with GPU capacity No Vendor Lock-In – ✅ Complete flexibility without API limits Performance Trade-Off – ⚠️ Open models slower than managed cloud APIs	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
Custom RAG – Multi-index strategies, tuned prompts for precision Domain fine-tuning – Eliminate hallucinations with proprietary data training Hybrid search – Semantic and keyword strategies tailored to data Source attribution – Full citations with confidence scores ⚠️ Ongoing tweaks – Perfecting retrieval accuracy takes time	Retrieval-Centric Generation – Research-backed approach separating LLM from knowledge memorization Mixtures-of-Knowledge-Bases – Multiple knowledge bases with intelligent routing Explicit Prompt-Weighting – Control retrieved content influence on answers Retrieval Transparency – ✅ Visual debugging showing document selection FAISS Search – Fast approximate nearest neighbor retrieval	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 bases – Self-hosted chatbots with custom internal docs Legacy integration – AI agents for ERPs, CRMs, ITSM tools Regulated industries – On-prem for healthcare, finance, government compliance Multi-lingual support – Any language with local LLM deployment Hybrid agents – Transactional workflows: IT tickets, approvals, automation	Air-Gapped Environments – ✅ Defense, classified research requiring offline operation Healthcare PHI Compliance – HIPAA organizations needing 100% data isolation RAG Research – Developers learning internals with full transparency Zero-Cost RAG – Teams with GPU infrastructure avoiding subscriptions Data Sovereignty – Strict data residency preventing cloud processing	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
On-prem deployment – Air-gapped environments, complete data control Custom compliance – HIPAA, GDPR, SOC 2, industry-specific measures Encryption – AES-256 at rest, TLS 1.3 in transit RBAC – Integrated with existing identity management systems ✅ Data residency – Full control over storage location (US, EU, on-prem)	Complete Data Isolation – ✅ Ideal for classified, PHI, PII data No Third-Party APIs – Zero external calls to cloud providers Open-Source Auditing – Full code transparency for security reviews Self-Managed Security – ⚠️ You control all security layers	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
Project pricing – $50K-$500K+ based on scope and complexity No subscriptions – Own solution outright without recurring fees Optional maintenance – Ongoing support contracts available post-launch ✅ 200+ clients – Fortune 500 and mid-market proven track record ⚠️ High upfront – Much costlier than $29-$999/mo SaaS platforms	MIT License – ✅ Free with no subscription or API charges GPU Costs Only – Hardware or cloud compute are sole expenses Unlimited Queries – No per-request pricing or rate limits	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
White-glove support – Direct dev team access throughout lifecycle Custom documentation – Tailored to your implementation and tech stack Training programs – IT teams and end users trained on solution Knowledge transfer – Complete handoff: code, architecture, runbooks ✅ Enterprise focus – Proven with large-scale, complex deployments	GitHub Repository – Code, docs, and examples at RCGAI/SimplyRetrieve Academic Paper – arXiv 2308.03983 explaining RCG architecture Community Support – GitHub Issues for troubleshooting No Paid Support – ⚠️ Community-driven only, no SLAs	Documentation hub – Docs, tutorials, API references Support channels – Email, in-app chat, dedicated managers (Premium+) Open-source – Python SDK, Postman, GitHub examples Community – User community + 5,000 Zapier integrations
Limitations & Considerations
⚠️ High upfront cost – $50K-$500K+ vs $29-$999/month SaaS ⚠️ Long time-to-value – 2-6 month build vs instant SaaS deployment ⚠️ Custom maintenance – Updates need dev work, no self-service ⚠️ No templates – Everything built from scratch, no no-code tools ⚠️ IT expertise required – Team needed for infrastructure and management Best for unique needs – Only justified when off-the-shelf fails	Developer-Only Tool – ⚠️ Requires Python, GPU, and technical expertise GPU Infrastructure Required – ⚠️ Dedicated hardware or cloud GPU needed Basic UI – Gradio interface needs custom front-end for production Manual Scaling – ⚠️ No auto-scaling, you manage load balancing No Enterprise Features – Missing multi-tenancy, user management, analytics Slower Inference – ⚠️ 3-10+ seconds vs sub-second cloud APIs	Managed service – Less control over RAG pipeline vs build-your-own Model selection – OpenAI + Anthropic only; no Cohere, AI21, open-source Real-time data – Requires re-indexing; not ideal for live inventory/prices Enterprise features – Custom SSO only on Enterprise plan
Core Agent Features
Autonomous agents – Planning modules, memory, RAG pipelines Agent Development Planning module – Task decomposition for multi-step autonomous workflows Memory system – Retains interactions for consistent long-running workflows Tool integration – CRMs, ERPs, ITSM, APIs, legacy systems RAG Implementation ✅ Proven deployment – Credit Agricole bank customer service automation	Retrieval-Centric Generation – Research approach separating reasoning from knowledge Retrieval Tuning Module – ✅ Developer transparency showing document selection Knowledge Base Mixing – Route queries across multiple sources Single-Turn Focus – ⚠️ Limited multi-turn conversation memory No Chatbot UI – ⚠️ Gradio for developers only No Production Features – ⚠️ No lead capture, handoff, or multi-channel support	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
Platform type – CUSTOM AI CONSULTANCY (not SaaS/platform) Core offering – Bespoke enterprise RAG and AI agents (200+ clients) Agent capabilities – Autonomous agents with planning, memory, tool integration Agent Services Developer experience – White-glove services, project-specific APIs, custom docs ⚠️ No no-code – Zero self-service, everything needs custom dev Deployment – On-prem/private cloud only, complete data sovereignty ✅ Enterprise ready – ISO 27001, GDPR/CCPA, custom HIPAA compliance ⚠️ NOT A PLATFORM – Exclusively custom consultancy, multi-month builds	NOT RAG-AS-A-SERVICE – Open-source research project for local experimentation Academic Foundation – Published research tool from RCGAI (arXiv 2308.03983) Self-Hosted Only – ⚠️ No managed infrastructure, APIs, or SLAs Developer-First Design – Python with GPU infrastructure requirements 100% Local Execution – ✅ Perfect for air-gapped and classified environments No Service Features – ⚠️ No auth, multi-tenancy, analytics, or SaaS conveniences	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

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Final Thoughts

Final Verdict: Deviniti vs SimplyRetrieve

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

When to Choose Deviniti

You value strong compliance and security focus
Self-hosted solutions for data privacy
Domain expertise in regulated industries

Best For: Strong compliance and security focus

When to Choose SimplyRetrieve

You value completely free and open source
Strong privacy focus - fully localized
Lightweight - runs on single GPU

Best For: Completely free and open source

Migration & Switching Considerations

Switching between Deviniti and SimplyRetrieve 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

Deviniti starts at custom pricing, while SimplyRetrieve 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 Deviniti and SimplyRetrieve 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: December 22, 2025 | 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.

Deviniti vs SimplyRetrieve