01
Context assembly is usually hidden
Many AI IDEs expose the answer, not the payload that shaped it. Teams review output without seeing the context decisions behind it.
Knotic • governed AI workspace
Govern AI delivery without giving up the speed of your editor.
Knotic gives software teams a VS Code-based workspace for prompt visibility, repo-native knowledge, multi-provider routing, and per-call telemetry in one operational surface.
Context Lens
Skills as Code
HQ Monitoring
BYOK
One governed workflow
See the context, reuse the knowledge, measure the spend.
This page keeps the product pitch static on purpose: no live hero telemetry, just the product surfaces teams use to govern day-to-day AI delivery.
Prompt visibility
Review payload, memory blocks, and token budget before a request is sent.
Repo-native knowledge
Keep plans, prompts, and conventions versioned where the team already works.
Provider control
Route roles across Knotic, OpenRouter, GitHub, Anthropic, OpenAI, or local runtimes.
Spend telemetry
Track tokens, latency, tools, and files touched for each workflow step.
Workspace outcomes
inspect
Review payloads before send.
share
Keep workflows and memory in the repo.
operate
Track cost, latency, and tool usage per call.
Why teams switch
AI coding is already standard. Governance is the missing layer.
Knotic is built for teams that need to understand what is being sent, preserve what works, and control spend without slowing down delivery.
02
Useful team knowledge does not compound
Prompts, plans, and conventions often stay trapped in private sessions, so every developer ends up re-teaching the same architecture.
03
Delivery speed can outrun governance
Hidden spend, provider lock-in, and cooldown windows make AI usage harder to operate at team scale.
Governed workflow
Three product surfaces hold the workflow together.
Knotic brings context review, reusable operating knowledge, and runtime monitoring into one place so AI work becomes visible and governable.
Context Lens
Inspect the exact request payload, memory blocks, and token budget before the model sees them.
- See what the model receives, not only the final answer.
- Trim or reorder noisy context before it weakens output.
- Make cost and quality tradeoffs explicit inside the workflow.
Skills as Code
Turn prompts, plans, and operating knowledge into versioned assets stored with the codebase.
- Review workflows in Git instead of losing them in chat history.
- Share conventions without restarting the same explanation every session.
- Give teams a reusable operating layer for AI work.
HQ Monitoring
Measure tokens, latency, tools, and file activity per call so delivery leads can manage AI operations with evidence.
- Make spend and throughput visible to engineering, finance, and security.
- Spot slow or over-contextualized workflows quickly.
- Understand which agents and skills are driving cost.
Production capabilities
The platform backs the workflow with real operational control.
The value is not only faster prompting. Knotic adds the infrastructure a team needs when privacy, provider choice, visibility, and throughput all matter at once.
Privacy-first architecture
Project memory and shared knowledge can stay in the repository, with support for local providers and no forced proprietary backend.
Multi-provider runtime
Assign different providers and models to different roles without rewriting the workflow.
No time-window lockouts
Keep delivery moving without arbitrary hourly or daily managed-inference cooldowns.
Architect mode
Break complex requests into sequenced plans that retain state between steps instead of relying on one oversized prompt.
Local model manager
Download and cache GGUF models for teams that need a practical path to private or air-gapped inference.
Remote session sharing
Collaborate on live AI sessions with permissions for viewing or interacting, so AI work becomes a shared team surface.
Control layer
Typical AI IDE speed, plus the controls teams ask for later.
Knotic adds the missing operational layer for organizations that want a faster workflow without handing context, spend, and team knowledge over to a black box.
Inspect the payload before sending it.
Keep shared knowledge versioned in the repository.
Expose per-call telemetry and cost visibility.
Route work across multiple providers explicitly.
Support local or air-gapped deployment paths.
Avoid managed-inference lockouts during delivery peaks.
Pricing
Pick the operating mode that fits your team.
Start free with Knotic, chat, and Context Lens. Paid plans add more credits for advanced workflows, support, and team-ready governance as usage grows.
Free
Start with Knotic without a subscription
€0
No subscription
Runtime cost follows the provider you choose
Use the workspace, in-app chat, and Context Lens for free when you bring your own provider or local runtime.
- Knotic workspace and in-app chat
- Context Lens before every send
- OpenRouter, GitHub, Anthropic, OpenAI, or local endpoints
- A VS Code-compatible workflow you can evaluate before buying credits
Tools
Tools
€9
/month
100 prompts
For teams that want Knotic tools and workflow while continuing to use a trusted provider.
- Discord community support
- Context Lens
- Pipeline multi-agent workflows
- Architect Mode
- VS Code compatibility
- Support for multiple model providers
- Brainstorming tool
Single seat
Basic
€20
/month
300 prompts
A lower-commitment plan for testing the full core workflow on one seat.
- Discord community support
- Context Lens
- Pipeline multi-agent workflows
- Architect Mode
- VS Code compatibility
- Support for multiple model providers
- Brainstorming tool
Single seat
Professional
€40
/month
650 prompts
For power users who want the complete Knotic workflow on a single seat.
- Discord community support
- Context Lens
- Pipeline multi-agent workflows
- Architect Mode
- VS Code compatibility
- Support for multiple model providers
- Brainstorming tool
Teams
Business
€100
/month
1500 prompts
For companies that need more volume, faster support, and room to scale governed AI delivery.
- Priority chat support (24 hours)
- Context Lens
- Pipeline multi-agent workflows
- Architect Mode
- VS Code compatibility
- Support for multiple model providers
- Brainstorming tool
FAQ
What teams ask before they trust another AI workspace.
Is Knotic another plugin or a full AI workspace?
Knotic is a VS Code-based AI workspace, not a single assistant panel. Planning, execution, context inspection, provider routing, shared knowledge, and telemetry live in the same surface.
What makes Knotic different from Cursor, Copilot, or Claude Code?
Knotic combines inspectable context, repo-versioned knowledge, multi-provider routing, visible execution, and governed operational controls in one workflow.
Can teams keep code and technical memory inside their own perimeter?
Yes. Knotic is designed for repo-native memory and supports local providers, which gives teams a path to keep code and knowledge under their own control.
Can we choose our own providers and models?
Yes. Knotic supports Knotic, OpenRouter, GitHub, Anthropic, OpenAI, and local runtimes, so teams can assign different providers to different roles.
How does Knotic help teams share knowledge?
Project memory, session context, specs, and skills can become repository artifacts or governed team surfaces instead of staying inside private chats.
Can Knotic help optimize AI and inference costs?
Yes. Context Lens helps trim unnecessary context before a request is sent, while HQ Monitoring exposes spend, latency, and activity per workflow.
Start with one governed workspace
Give your team one place to inspect, reuse, and operate AI work.
Use Knotic when the team needs prompt visibility, provider choice, shared knowledge, and telemetry without leaving the editor model they already understand.
Built by Artiforge
VS Code-based workflow
Governed AI delivery