Coveo vs Deviniti

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 Coveo and Deviniti 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 Coveo and Deviniti, 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 Coveo if: you value comprehensive enterprise search capabilities
  • Choose Deviniti if: you value strong compliance and security focus

About Coveo

Coveo Landing Page Screenshot

Coveo is ai-powered search and personalization for digital experiences. Coveo is an enterprise AI platform that delivers intelligent search, recommendations, and personalization across commerce, customer service, workplace, and website applications using machine learning and behavioral analytics. Founded in 2005, headquartered in Quebec City, Canada, the platform has established itself as a reliable solution in the RAG space.

Overall Rating
82/100
Starting Price
Custom

About Deviniti

Deviniti Landing Page Screenshot

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

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: Enterprise Search versus AI Development. 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

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Coveo
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Deviniti
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Data Ingestion & Knowledge Sources
  • 100+ Native Connectors – SharePoint, Salesforce, ServiceNow, Confluence, databases, file shares, Slack, websites merged into one index
  • OCR & Structured Data – Indexes scanned docs, intranet pages, knowledge articles, multimedia content
  • Real-Time Sync – Incremental crawls, push APIs, scheduled syncs keep content fresh
  • 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
  • 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
  • Atomic UI Components – Drop-in components for search pages, support hubs, commerce sites with generative answers
  • Native Platform Integrations – Salesforce, Sitecore with AI answers inside existing tools
  • REST APIs – Build custom chatbots, virtual assistants on Coveo's retrieval engine
  • 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
  • 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
  • Uses Relevance Generative Answering (RGA)—a two-step retrieval plus LLM flow that produces concise, source-cited answers.
  • Respects permissions, showing each user only the content they’re allowed to see.
  • Blends the direct answer with classic search results so people can dig deeper if they want.
  • 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
  • ✅ #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
  • Atomic components are fully styleable with CSS, making it easy to match your brand’s look and feel.
  • You can tweak answer formatting and citation display through configs; deeper personality tweaks mean editing the prompt.
  • 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
  • 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
  • Azure OpenAI GPT – Primary models via Azure OpenAI for high-quality generation
  • Bring Your Own LLM – Relevance-Augmented Passage Retrieval API supports custom models
  • Auto-Tuning – Handles model tuning, prompt optimization; API override available
  • 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
  • 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 APIs & SDKs – Java, .NET, JavaScript for indexing, connectors, querying
  • UI Components – Atomic and Quantic components for fast front-end integration
  • Enterprise Documentation – Step-by-step guides for pipelines, index management
  • 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
  • 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
  • Pairs keyword search with semantic vector search so the LLM gets the best possible context.
  • Reranking plus smart prompts keep hallucinations low and citations precise.
  • Built on a scalable architecture that handles heavy query loads and massive content sets.
  • 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
  • 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)
  • Fine-tune which sources and metadata the engine uses via query pipelines and filters.
  • Integrates with SSO/LDAP so results are tailored to each user’s permissions.
  • Developers can tweak prompt templates or inject business rules to shape the output.
  • Total control – Add sources, tweak tone, inject APIs Details
  • Unlimited flexibility – Dream it, Deviniti builds it
  • ⚠️ Dev sprints – Updates usually require quick development work
  • 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
  • Enterprise Licensing – Pricing based on sources, query volume, features
  • 99.999% Uptime – Scales to millions of queries, regional data centers
  • Annual Contracts – Volume tiers with optional premium support
  • 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
  • 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
  • ISO 27001/27018, SOC 2 – Plus HIPAA-compatible deployments available
  • Permission-Aware – Granular access controls, users see only authorized content
  • Private Cloud/On-Prem – Deployment options for strict data-residency requirements
  • 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
  • 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
  • Analytics Dashboard – Tracks query volume, engagement, generative-answer performance
  • Pipeline Logs – Exportable for deeper analysis and troubleshooting
  • A/B Testing – Query pipeline experiments to measure impact, fine-tune relevance
  • Custom monitoring – CloudWatch, Prometheus integration Info
  • Admin dashboards – Real-time analytics, alerts, SIEM feeds
  • Enterprise tools – Integrates with existing monitoring infrastructure
  • 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
  • Enterprise Support – Account managers, 24/7 help, extensive training programs
  • Partner Network – Coveo Connect community with docs, forums, certified integrations
  • Regular Updates – Product releases and industry events for latest trends
  • 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
  • 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
  • Coveo goes beyond Q&A to power search, recommendations, and discovery for large digital experiences.
  • Deep integration with enterprise systems and strong permissioning make it ideal for internal knowledge management.
  • Feature-rich but best suited for organizations with an established IT team to tune and maintain it.
  • 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
  • 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
  • Admin Console – Atomic components enable minimal-code starts
  • ⚠️ Developer Involvement – Full generative setup requires technical resources
  • Best For – Teams with existing IT resources, more complex than pure no-code
  • ⚠️ No no-code tools – IT or admin panels handle configuration
  • User experience – End users chat; tech team manages tweaks
  • 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 – Enterprise AI-powered search/discovery with RGA for large-scale knowledge management
  • Target Customers – Large enterprises with complex content (SharePoint, Salesforce, ServiceNow, Confluence) needing permission-aware search
  • Key Competitors – Azure AI Search, Vectara.ai, Glean, Elastic Enterprise Search
  • Competitive Advantages – 100+ connectors, hybrid search, permission-aware results, 99.999% uptime SLA
  • Pricing – Enterprise licensing higher than SaaS chatbots; best value for unified search across massive content
  • Use Case Fit – Knowledge hubs, support portals, commerce sites with generative answers
  • 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 – 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
  • Azure OpenAI GPT – Primary models via Azure OpenAI for high-quality generation
  • Model Flexibility – Relevance-Augmented Passage Retrieval API supports custom LLMs
  • Auto-Tuning – Handles model tuning, prompt optimization automatically; API override available
  • Search Integration – LLM tightly integrated with keyword + semantic search pipeline
  • 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
  • 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
  • RGA (Relevance Generative Answering) – Two-step retrieval + LLM producing source-cited answers
  • Hybrid Search – Keyword + semantic vector search for optimal LLM context
  • Reranking & Smart Prompts – Keeps hallucinations low, citations precise
  • Permission-Aware – SSO/LDAP integration shows only authorized content per user
  • Query Pipelines – Fine-tune sources, metadata, filters for retrieval control
  • 99.999% Uptime – Scalable architecture for heavy query loads, massive content sets
  • 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
  • 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
  • Industries – Financial Services, Telecommunications, High-Tech, Retail, Healthcare, Manufacturing
  • Internal Knowledge – Enterprise systems integration, permissioning for documentation, knowledge hubs
  • Customer Support – Support hubs with generative answers from knowledge bases, ticket history
  • Commerce Sites – Product search, recommendations, AI-powered discovery features
  • Content Scale – Large distributed content across SharePoint, databases, file shares, Confluence, ServiceNow
  • Team Sizes – Large enterprises with IT teams, millions of queries
  • 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
  • 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
  • ISO 27001/27018, SOC 2 – International security, privacy standards for enterprises
  • HIPAA-Compatible – Deployments available for healthcare compliance requirements
  • Granular Access Controls – Permission-aware search, SSO/LDAP integration
  • Private Cloud/On-Prem – Options for strict data-residency requirements
  • 99.999% Uptime SLA – Regional data centers for mission-critical infrastructure
  • 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)
  • 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
  • Enterprise Licensing – $600 to $1,320 depending on sources, query volume, features
  • Pro Plan – Entry-level with core search, RGA for smaller enterprises
  • Enterprise Plan – Full-featured with advanced capabilities, higher volumes, premium support
  • Annual Contracts – Volume tiers with optional premium support packages
  • ⚠️ Consumption-Based – Pricing model can make costs hard to predict
  • Best Value For – Unified search across massive content, millions of queries
  • 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
  • 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
  • Enterprise Support – Account managers, 24/7 help, guaranteed response times
  • Partner Network – Certified integrations via Coveo Connect community
  • Documentation – Step-by-step guides for pipelines, index management, connectors
  • Training Programs – Admin console, Atomic components, developer integration
  • Regular Updates – Product releases, industry events for latest trends
  • 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
  • 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
  • ⚠️ Developer Involvement – Full generative setup requires technical resources
  • ⚠️ Cost Predictability – Consumption-based pricing hard to predict for enterprise scale
  • ⚠️ IT Team Needed – Best for organizations with established technical teams
  • ⚠️ Enterprise Focus – Optimized for enterprises vs. SMBs or startups
  • NOT Ideal For – Small businesses, plug-and-play chatbot needs, immediate no-code deployment
  • ⚠️ 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
  • 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
  • Agentic AI Integration – Coveo for Agentforce, expanded API suite, Design Partner Program (2024-2025)
  • Agent API Suite – Search API, Passage Retrieval API, Answer API for grounding agents
  • Salesforce Agentforce – Native integration for customer service, sales, marketing agents
  • AWS RAG-as-a-Service – MCP Server for Amazon Bedrock AgentCore, Agents, Quick Suite (Dec 2024)
  • Four Tools – Passage Retrieval, Answer gen (Amazon Nova), Search, Fetch
  • Security-First – Inherits document/item-level permissions automatically for trusted answers
  • 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
  • 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 – Enterprise search with RAG-as-a-Service, Relevance Generative Answering (RGA)
  • RAG Launch – AWS RAG-as-a-Service announced December 1, 2024 as cloud-native offering
  • 40% Accuracy Improvement – RAG increases base model accuracy according to industry studies
  • Hybrid Search – Keyword, vector, hybrid search with relevance tuning
  • 100+ Connectors – SharePoint, Salesforce, ServiceNow, Confluence, databases, Slack
  • Best For – Enterprises with distributed content needing permission-aware search, knowledge hubs, generative answers
  • 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
  • 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: Coveo vs Deviniti

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

When to Choose Coveo

  • You value comprehensive enterprise search capabilities
  • Strong e-commerce and B2B features
  • Deep Salesforce integration

Best For: Comprehensive enterprise search capabilities

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

Migration & Switching Considerations

Switching between Coveo and Deviniti 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

Coveo starts at custom pricing, while Deviniti 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 Coveo and Deviniti 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 28, 2025 | 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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