DokBot vs Koreshield: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of DokBot and Koreshield — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
DokBot
DokBot
DokBot turns your PDFs and documents into an embeddable RAG support chatbot for your website in minutes, using your own API key or built-in credits.
Key features
- Multi-Format RAG Knowledge Bases: Native ingestion of PDF, DOCX, XLSX, MD and TXT files with automatic processing and chunking — no copy-pasting text.
- Bring Your Own API Key: Connect OpenAI, Anthropic, Google AI Studio, Groq, OpenRouter, CheaperInference or Ollama Cloud directly without a middleman.
- Managed AI Credits: Optionally buy monthly AI credits so DokBot runs the model on its own provider key and bots need no API key.
- Human Handoff: When the bot doesn't know an answer it collects the visitor's email and surfaces the full conversation in the Conversations inbox.
- Shadow DOM Embeddable Widget: Install with one script tag before </body>, fully isolated so it never breaks your site's CSS.
- Live Preview Testing: Iterate on prompts and verify answer accuracy in a live preview before going public.
- MCP Access: Pro plan exposes MCP so your own AI assistant can manage bots and knowledge bases.
Best for
- Website Customer Support: Answer common visitor questions 24/7 from product manuals and help docs.
- Documentation Assistant: Let users query long technical PDFs or guides conversationally instead of searching manually.
- Lead Capture from Unanswered Questions: Collect emails when the bot can't answer and follow up with full context.
- Low-Cost Support Automation: Small businesses run a support bot on free-tier or cheap model providers via BYOK.
- Multilingual SMB Support: Spanish-speaking businesses deploy a docs-grounded assistant on their site in minutes.
- Agency Client Bots: Build and manage multiple bots with separate knowledge bases for different client sites.
Koreshield
Koreshield Labs Ltd.
Runtime trust layer that scans customer input, retrieved context and proposed tool calls in AI support workflows before they become trusted instructions.
Key features
- Customer Input Scanning: Inspects messages, attachments and externally controlled text before model execution so injected instructions never reach the model as trusted input.
- Retrieved Context Screening: Keeps poisoned tickets, CRM notes and RAG documents from inheriting system-level authority inside the prompt.
- Proposed Action Evaluation: Checks tool calls against trust, approval and authorization limits before they are executed.
- Detect and Enforce Modes: Run in detect mode to record threats without interrupting traffic, then enable enforcement only where fallback behavior is ready.
- Decision Evidence Trail: Records severity, decision and reason for every request, retained for 7 or 30 days depending on plan, for review and audits.
- Scan API with Key Management: Server-side API keys and endpoints such as /v1/rag/scan make integration with existing support stacks straightforward.
- Flexible Deployment: Use the hosted console or run the FastAPI + PostgreSQL service in your own infrastructure, with VPC, self-hosted and air-gapped options for Enterprise.
Best for
- Prompt Injection Defense: Blocking malicious instructions hidden in customer messages before an AI support agent acts on them.
- RAG Poisoning Protection: Preventing tampered knowledge-base articles or ticket histories from overriding system prompts.
- Agent Action Guardrails: Holding refunds, account changes or other tool calls for policy review when trust limits are exceeded.
- Safe Production Rollout: Measuring real threat and false-positive rates in detect mode before enforcing on live traffic.
- Security Audits: Exporting decision evidence to show auditors and security teams why each request was allowed or held.