Data Ingestion & Knowledge Sources
✅ Point-and-click RAG builder – Mix SharePoint, Confluence, databases via visual pipeline [MongoDB Reference]
✅ Fine-grained control – Configure chunk sizes, embedding strategies, multiple sources simultaneously
✅ Multi-source blending – Combine documents and live database queries in same pipeline
File Support – PDF, Word, text, JSON, YAML, CSV; full website crawling
Cloud Integrations – Native Google Drive, Notion, Confluence, Guru (⚠️ no Dropbox)
Chat2KB (Growth/Enterprise) – Auto-extracts Q&A from conversations with conflict resolution
Real-time Updates – Starter 50 docs → Growth 1K → Enterprise unlimited
⚠️ YouTube transcripts NOT supported – LLMs "not great at video interpretation"
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
✅ API-first architecture – Surface agents via REST or GraphQL endpoints [MongoDB: API Approach]
⚠️ No prefab UI – Bring or build your own front-end chat widget
✅ Universal integration – Drop into any environment that makes HTTP calls
20+ Native Helpdesk Integrations – Zendesk, Intercom, Salesforce, Front, Gorgias, HubSpot (⚠️ no Zapier)
Omnichannel – Slack, Discord, Teams; WhatsApp/Messenger via Zendesk/Intercom (⚠️ not Telegram)
Website Options – Fini Widget, Search Bar, Standalone; Chrome Extension for agents
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
✅ Agentic architecture – Multi-step reasoning, tool use, dynamic decision-making [Agentic RAG]
✅ Intelligent routing – Agents decide knowledge base vs live DB vs API
✅ Complex workflows – Fetch structured data, retrieve docs, blend answers automatically
Sophie AI Agent – 5-layer execution: Safety, LLM Supervisor, Skills, Feedback, Traceability
100+ Languages – Locale-based routing with real-time translation
Human Handoff – Context-preserving escalation via keywords, sentiment, confidence thresholds
✅ 80% Ticket Resolution – End-to-end without human intervention claim
✅ #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
✅ 100% front-end control – No built-in UI means complete look and feel ownership
✅ Deep behavior tweaks – Customize prompt templates and scenario configs extensively
✅ Multiple personas – Create unlimited agent personas with different rule sets
GUI Widget Editor – Logo, colors, title, messages, FAQs (⚠️ CSS not documented)
White-Labeling – Custom domain (CNAME), full logo replacement, agent identity renaming
100+ Tone Options – Friendly, Professional, TaxAssistant, Finance advisor, Casual, polite
Dynamic Routing – User context (VIP, first-time, veteran) for metadata-driven personalization
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
✅ Model-agnostic – Plug in GPT-4, Claude, open-source models freely
✅ Full stack control – Choose embedding model, vector DB, orchestration logic
⚠️ More setup required – Power and flexibility trade-off vs turnkey solutions
Starter (Free) – GPT-4o mini only
Growth – GPT-4o mini + Claude
Enterprise – GPT-4o + Multi-layer automatic routing per query part
RAGless Architecture – Query-writing AI; "no embeddings, no hallucinations"
⚠️ No Runtime Switching – Plan-based selection only
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-code pipeline builder – Design pipelines visually, deploy to single API endpoint
✅ Sandbox testing – Rapid iteration and tweaking before production launch
⚠️ No official SDK – REST/GraphQL integration straightforward but no client libraries
Base URL – https://api-prod.usefini.com (v2, Bearer Token auth)
Core Endpoints – /v2/bots/ask-question, /v2/bots/links/*, feedback, chat history
⚠️ NO Official SDKs – Only Python and Node.js examples
Documentation Quality – 3/5 completeness, 2/5 error handling, 1/5 rate limits
Paramount – Open-source tool (github.com/ask-fini/paramount) for accuracy measurement
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
✅ Hybrid retrieval – Mix semantic, lexical, or graph search for sharper context
✅ Threshold tuning – Balance precision vs recall for your domain requirements
✅ Enterprise scaling – Vector DBs and stores handle high-volume workloads efficiently
✅ 97-98% Accuracy Claim – Column Tax (94%, 98% resolved), Qogita (90%, 121% SLA)
6 Hallucination Prevention – RAGless, LLM filtering, confidence gating, guardrails, skill modules
Accuracy Tools – Sophia AI Evaluator (Growth/Enterprise), Paramount, CXACT Benchmarking
✅ 80% Ticket Resolution – End-to-end without human intervention
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)
✅ Multi-step reasoning – Scenario logic, tool calls, unified agent workflows
✅ Data blending – Combine structured APIs/DBs with unstructured docs seamlessly
✅ Full retrieval control – Customize chunking, metadata, and retrieval algorithms completely
Guidelines System – Tone, phrases, forbidden terms, formatting, response length
Bot Management – Starter 2 bots → Growth/Enterprise unlimited
Real-time Learning – Chat2KB auto-learning (MECE), Flows for specialized workflows
Dynamic Personalization – User context from backend, segment-based routing
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
⚠️ Custom contracts only – No public tiers, typically usage-based enterprise pricing
✅ Massive scalability – Leverage your own infrastructure for huge data and concurrency
✅ Best for large orgs – Ideal for flexible architecture and pricing at scale
⚠️ Pricing NOT Publicly Disclosed – Requires sales contact
Starter (Free) – GPT-4o mini, ~50 questions/month, ~50 docs, 2 bots
Growth (est. $999/mo) – GPT-4o mini/Claude, 1K docs, unlimited users, SOC 2, RBAC, Chat2KB
Enterprise (Custom) – GPT-4o, Multi-layer models, unlimited docs, AI Actions, white-glove onboarding
✅ Zero-Pay Guarantee – Only pay if >80% accuracy met
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
✅ Enterprise-grade security – Encryption, compliance, access controls included [MongoDB: Enterprise Security]
✅ Data sovereignty – Keep data in your environment with bring-your-own infrastructure
✅ Single-tenant VPC – Supports strict isolation for regulatory compliance requirements
✅ Certifications – SOC 2 Type II (zero findings), ISO 27001, ISO 42001, GDPR
⚠️ HIPAA Conflicting – Marketing claims vs. case study "next up" (verify)
⚠️ PCI DSS – Claimed but not on official security section (verify)
PII Shield – Auto-masks SSN, passport, license, taxpayer ID, credit cards
Encryption – AES-256 at rest, TLS 1.3 in transit; "no training" policy
Access Controls – RBAC (Growth/Enterprise), SSO, audit logging, EU/US data residency
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
✅ Pipeline-stage monitoring – Track chunking, embeddings, queries with detailed visibility [MongoDB: Lifecycle Tools]
✅ Step-by-step debugging – See which tools agent used and why decisions made
✅ External logging integration – Hooks for logging systems and A/B testing capabilities
Fini 2.0 (Jan 2025) – AI resolution, quality, confidence, CSAT, agent productivity, drop-off analysis
Chat History (Feb 2025) – Centralized view with filtering; CSV/JSON export for Looker/Tableau
AI Categorization – Auto-tags by topic (returns, login, pricing, shipping)
Knowledge Gap Analysis – Identifies unanswerable questions with improvement suggestions
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
✅ Tailored onboarding – Enterprise-focused with solution engineering for large customers
✅ MongoDB partnership – Tight integrations with Atlas Vector Search and enterprise support [Case Study]
⚠️ Limited public forums – Direct engineer-to-engineer support vs broad community resources
Founding Team – Ex-Uber engineers; CEO led 4M+ interactions/month at Uber
Backed By – Y Combinator S22 ($125K), Matrix Partners, angels from Uber/Intercom/Softbank
Customers – HackerRank, Qogita, Column Tax, Bitdefender, Duolingo, Meesho, TrainingPeaks
Implementation – 60-day program; Enterprise gets dedicated AI engineers, 24/7 Slack
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
✅ Graph-optimized retrieval – Specialized for interlinked docs with relationships [MongoDB Reference]
✅ AI orchestration layer – Call APIs or trigger actions as part of answers
⚠️ Requires LLMOps expertise – Best for teams wanting deep customization, not prefab chatbots
✅ Tailor-made agents – Focuses on custom AI agents vs out-of-box chat tool
RAGless Positioning – Criticizes RAG as "search engines" claiming "will become obsolete"
Action-Taking Focus – Actions vs. information ("Done! Refund processed" vs. "Find details here")
Target Customer – Enterprise B2C high-volume (fintech, e-commerce, healthcare)
vs. Intercom Fin – Claims 95%+ accuracy vs. ~80%; platform agnostic
⚠️ Less Suitable For – General Q&A, content generation, standalone chatbots
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
✅ Low-code builder – Set up pipelines, chunking, data sources without heavy coding
⚠️ Technical knowledge needed – Understanding embeddings and prompts helps significantly
⚠️ No end-user UI – You build front-end while Dataworkz handles back-end logic
✅ Time to Go Live – "2 minutes" setup, <1 week full integration, 1-2 weeks Enterprise
No-Code Deployment – Widget (JS snippet), Search Bar, Standalone, native helpdesk one-click, Chrome Extension
Admin Dashboard – Agent creation, Knowledge Hub (Notion/Confluence/Drive), Prompt Configurator (escalation, guardrails)
Pre-Built Templates – E-commerce, fintech, SaaS onboarding workflows
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
Market position – Enterprise agentic RAG platform with point-and-click pipeline builder
Target customers – Large enterprises with LLMOps expertise building complex AI agents
Key competitors – Deepset Cloud, LangChain/LangSmith, Haystack, Vectara.ai, custom RAG solutions
Core advantages – Model-agnostic, agentic architecture, graph retrieval, no-code builder, MongoDB partnership
Best for – High-volume complex use cases with existing infrastructure and orchestration needs
Market Position – Agentic AI for customer support; Sophie's 5-layer + RAGless claiming 97-98% accuracy
Key Competitors – Intercom Fin, Zendesk Answer Bot, Ada, Ultimate.ai, traditional RAG chatbots
✅ Competitive Advantages – 97-98% accuracy vs. ~80%, 20+ native integrations, RAGless, 100+ languages, Zero-Pay Guarantee
Best Value For – Enterprises prioritizing accuracy, action-taking AI, regulated industries (fintech, healthcare)
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
✅ Model-agnostic – GPT-4, Claude, Llama, open-source models fully supported
✅ Public APIs – AWS Bedrock and OpenAI API integration for managed access
✅ Private hosting – Host open-source models in your VPC for sovereignty
✅ Composable stack – Choose embedding, vector DB, chunking, LLM independently
✅ No lock-in – Switch models without platform migration for cost or compliance
Starter (Free) – GPT-4o mini only (~50 questions/month)
Growth – GPT-4o mini + Claude, 1K docs, unlimited users
Enterprise – GPT-4o + Multi-layer automatic routing per query part
✅ Target Accuracy – 97-98% claim with human-in-the-loop customization
⚠️ No Manual Switching – Plan-based model selection only
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
✅ Advanced pipeline builder – Point-and-click RAG configuration with fine-grained control RAG-as-a-Service
✅ Agentic architecture – Multi-step tasks, external tool calls, adaptive reasoning [Agentic RAG]
✅ Hybrid retrieval – Semantic, lexical, graph search for accuracy and context
✅ Graph-optimized – Relationship-aware context for interlinked documents [Graph Capabilities]
✅ Dynamic tool selection – Agents choose knowledge base, DB, or API automatically
RAGless Architecture – Query-writing AI; "no embeddings, no hallucinations" with precise attribution
6-Mechanism Prevention – LLM filtering, confidence gating, guardrails, deterministic skill modules
Real-time Knowledge – Content used immediately after ingestion without retraining
Chat2KB (Growth/Enterprise) – Auto-extracts Q&A with MECE classification, conflict resolution
✅ Customer Results – Column Tax (94%, 98% resolved), Qogita (90%, 121% SLA)
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
Retail – Product recommendations, inventory queries with structured/unstructured data blending [Retail Case Study]
Banking – Regulatory compliance, risk assessment with enterprise security and auditability
Healthcare – Clinical decision support, medical knowledge bases with HIPAA compliance
Enterprise knowledge – Documentation, policy queries with multi-source integration (SharePoint, Confluence, databases)
Customer support – Multi-step troubleshooting, automated responses with tool calling and APIs
Legal – Contract analysis, regulatory research with audit trails and traceability
✅ Enterprise B2C Support – High-volume fintech, e-commerce, healthcare (80% resolution, 97-98% accuracy)
✅ Action-Taking AI – Autonomous refunds, updates, CRM sync (Salesforce, Stripe, Shopify)
✅ Helpdesk Integration – 20+ native platforms (Zendesk, Intercom, Salesforce, Front) without Zapier
✅ PII-Sensitive Industries – Auto-masking SSN, passport, license, credit cards with PII Shield
⚠️ NOT Suitable For – General Q&A, content generation, no existing helpdesk
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
✅ Enterprise-grade – Encryption, compliance, access controls for large organizations [Security Features]
✅ Audit trails – Every interaction, tool call, data access audited for transparency
✅ Data sovereignty – Bring-your-own-infrastructure keeps data in your environment completely
✅ Compliance ready – Architecture supports GDPR, HIPAA, SOC 2 through flexible deployment
✅ SOC 2 Type II – Zero audit findings per Sprinto
✅ ISO 27001 & 42001 – Information security + AI governance
✅ GDPR Compliant – Full data subject rights, EU data residency
⚠️ HIPAA Conflicting – Marketing claims vs. case study "next up" (verify)
⚠️ PCI DSS – Claimed but not on official security page (verify)
"No Training on Data" – OpenAI DPA; PII Shield; AES-256, TLS 1.3
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
⚠️ Custom contracts – Tailored pricing, no public tiers, requires sales engagement
✅ Credit-based usage – 2M rows per credit for data movement, usage-based model
✅ AWS Marketplace – Available for streamlined enterprise procurement [AWS Marketplace]
✅ BYOI savings – Use existing infrastructure (databases, vector stores) to reduce costs
⚠️ Pricing NOT Publicly Disclosed – Requires sales contact
Starter (Free) – GPT-4o mini, ~50 questions/month, ~50 docs, 2 bots
Growth (est. $999/mo) – GPT-4o mini/Claude, 1K docs, unlimited users, SOC 2, RBAC, Chat2KB
Enterprise (Custom) – GPT-4o, Multi-layer models, unlimited docs, AI Actions, white-glove onboarding
✅ Zero-Pay Guarantee – Only pay if >80% accuracy met (unique risk mitigation)
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
✅ Enterprise onboarding – Tailored solution engineering for large organizations with complex needs
✅ Direct engineering support – Engineer-to-engineer technical implementation and optimization assistance
✅ Product documentation – Platform setup, pipeline config, agentic workflows covered [Product Docs]
✅ MongoDB partnership – Joint support for Atlas Vector Search and enterprise deployments
Founding Team – Ex-Uber engineers; CEO led 4M+ interactions/month; Y Combinator S22, Matrix Partners
Customers – HackerRank, Qogita, Column Tax, Bitdefender, Duolingo, Meesho
60-Day Implementation – Discovery → Deployment → Optimization → Production with dedicated managers
Enterprise Support – Dedicated AI engineers, CSMs, 24/7 Slack channels
⚠️ Documentation Quality – 3/5 completeness, 2/5 error handling, 1/5 rate limits; NO SDKs
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 built-in UI – API-first platform requires you to build front-end interface
⚠️ Technical expertise required – Best for LLMOps teams understanding embeddings, prompts, RAG architecture
⚠️ Custom pricing only – No transparent public tiers, requires sales engagement for quotes
⚠️ Enterprise focus – May be overkill for small teams or simple chatbot cases
⚠️ Infrastructure requirements – BYOI model needs existing cloud infrastructure and data engineering capabilities
⚠️ Pricing Opacity – No public pricing creates evaluation friction
⚠️ HIPAA & PCI DSS Unverified – Conflicting claims require verification
⚠️ Documentation Limitations – Basic API docs (3/5, 2/5, 1/5), no SDKs
⚠️ Small Team (14 employees) – Limited capacity vs. enterprise competitors
⚠️ Platform Lock-In – Requires existing helpdesk (Zendesk/Intercom/Salesforce)
✅ Best For – Enterprise B2C high-volume prioritizing 97-98% accuracy, 60-day commitment
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
✅ Agentic RAG – Multi-step reasoning, external tools, adaptive context-based operation [Agentic Capabilities]
✅ Agent memory – Conversational history, user preferences, business context via RAG pipelines
✅ DAG task execution – Complex tasks decomposed into interdependent sub-tasks with parallelization [Multi-Step Reasoning]
✅ LLM Compiler – Identifies optimal sub-task sequence with parallel execution when possible
✅ External API integration – Create CRM leads, support tickets, trigger actions dynamically [Agent Builder]
✅ Continuous learning – Agent frameworks support context switching and adaptation over time
Sophie AI Agent – Fully autonomous resolving 80% of tickets end-to-end without human intervention
5-Layer Execution – Safety Guardrails (40+ filters, PII), LLM Supervisor, Skills, Feedback, Traceability
Multi-Layer Architecture (Enterprise) – Automatic routing to best LLM per query part; specialized agents
Action-Taking – Autonomous refunds, updates, CRM sync (Salesforce, Stripe, Shopify)
✅ 100+ Languages – Automatic translation with locale-based routing
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 – TRUE RAG-AS-A-SERVICE: Enterprise agentic orchestration layer for custom agents
Core architecture – Model-agnostic with full control over LLM, embeddings, vector DB, chunking
Agentic focus – Autonomous agents with multi-step reasoning, not simple Q&A chatbots [Agentic RAG]
Developer experience – Point-and-click builder, sandbox testing, REST/GraphQL API, agent builder UI
Target market – Large enterprises with data teams building sophisticated agents requiring deep customization
RAG differentiation – Graph retrieval, hybrid search, threshold tuning, agentic DAG execution
Platform Type – AGENTIC AI CUSTOMER SUPPORT with RAGless architecture, NOT traditional RAG-as-a-Service
Architectural Approach – Query-writing AI; "no embeddings, no hallucinations" with deterministic results
Sophie's 5-Layer Framework – 97-98% accuracy vs. ~80% competitors; Zero-Pay Guarantee
⚠️ Developer Experience – Basic REST API (v2), NO SDKs, docs (3/5, 2/5, 1/5)
No-Code Capabilities – "2 minutes" setup, 20+ native helpdesk integrations, "Day 1 Ready-to-Use"
⚠️ NOT A RAG PLATFORM – Explicitly positions AGAINST traditional RAG; fundamentally different
⚠️ NOT Suitable For – General Q&A, content generation, no helpdesk, programmatic RAG API needs
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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