Copy-pasting context into Claude, ChatGPT, or Gemini is slow, unsafe, and
token-blind. Mesh assembles a reusable stack from your knowledge sources
and scans for secrets
before anything leaves your machine.
Every time you assemble a prompt manually, you're fighting the same five problems.
The Problem
Mesh Fixes It
No repeatable context process
Every session starts from scratch. Hunting the same files, re-pasting the same Notion pages, hoping you didn't miss anything. There's no saved process, no consistency, and no way to know if this prompt matches the last one.
No repeatable context process
Every session starts from scratch. Hunting the same files, re-pasting the same Notion pages, hoping you didn't miss anything. There's no saved process, no consistency, and no way to know if this prompt matches the last one.
Mesh stacks are saved and reusable. Build once, reuse across sessions - same sources, same structure, every time.
Token limit overflows
You have no visibility into how much context you're sending until the API rejects your request or you get a truncated response.
Token limit overflows
You have no visibility into how much context you're sending until the API rejects your request or you get a truncated response.
Mesh shows real-time, model-aware token counts before you export.
Accidental secret leakage
API keys, PII, and internal file paths silently slip into prompts sent to public LLM APIs — without any warning.
Accidental secret leakage
API keys, PII, and internal file paths silently slip into prompts sent to public LLM APIs — without any warning.
Mesh's Privacy Scanner detects and replaces sensitive tokens before export.
Stale context
Files added to a prompt are snapshots. By the time you send the request, the code or document may have changed.
Stale context
Files added to a prompt are snapshots. By the time you send the request, the code or document may have changed.
JIT reading fetches content at assembly time, with reload on demand.
Degraded context mid-conversation
As conversations grow, LLMs silently compress earlier context to fit the window - leading to errors, hallucinations, and contradictions you can't easily trace
Degraded context mid-conversation
As conversations grow, LLMs silently compress earlier context to fit the window - leading to errors, hallucinations, and contradictions you can't easily trace
Your Mesh stack is always ready to reassemble. When context drifts, reset with a fresh, precise payload in a few clicks - no rebuilding from scratch.
How It Works
From source to export in four steps.
01
Connect your sources
Link your Notion workspace, point Mesh at local directories with glob patterns, or pull from your saved Context Blocks library. All sources are readable on demand.
02
Assemble your stack
Drag items into The Stack, reorder them, pin the ones you always need, and remove anything stale. Every item is fetched just-in-time, always the latest version.
03
Check token limits
The model-aware token counter updates live as you add and remove items. Trim in the Output Editor until you're comfortably within your target model's limit.
04
Secure export via Exit Gate
Before anything leaves your machine, the Privacy Scanner checks for secrets, PII, and internal paths. The Exit Gate blocks unsafe exports. Clean context lands in your LLM client.
Mesh handles the entire context workflow — from ingestion to secure export.
Multi-Source Ingestion
Connect Notion databases, glob local files from your filesystem, and pull from your saved Context Blocks library. One unified assembly area for all your knowledge sources.
Privacy & Security Scanner
Automatically detect API keys, PII, and internal paths before they leave your machine. Consistent token replacement, custom rules, and an Exit Gate that blocks unsafe exports.
The Stack
A central staging area where you compose, reorder, pin, and bulk-manage context items. Save scoped stacks for reuse across projects and sessions.
Token Management
Model-aware token counts give you real-time feedback as you build. Use the Output Editor to trim, then export directly to your LLM client or clipboard.
Multi-Source Ingestion
Connect Notion databases, glob local files from your filesystem, and pull from your saved Context Blocks library. One unified assembly area for all your knowledge sources.
Privacy & Security Scanner
Automatically detect API keys, PII, and internal paths before they leave your machine. Consistent token replacement, custom rules, and an Exit Gate that blocks unsafe exports.
The Stack
A central staging area where you compose, reorder, pin, and bulk-manage context items. Save scoped stacks for reuse across projects and sessions.
Token Management
Model-aware token counts give you real-time feedback as you build. Use the Output Editor to trim, then export directly to your LLM client or clipboard.
Built For Your Team
Mesh fits into how your team already works with AI.
Product Managers
You're wasting hours copy-pasting from Notion into AI tools just to hit token limits. Mesh automatically bundles your specs and research into perfect feature briefs.
Developers
Stop feeding your LLM stale, copy-pasted code. Glob local files just-in-time and give your AI the exact context it needs - fresh files, right-sized for the model.
Security Teams
Hoping your team won't paste API keys into ChatGPT isn't a strategy. The Privacy Scanner detects and masks sensitive data before anything leaves your machine.
Startup Founders
You're rebuilding the exact same context stack for every AI session. Save your core company knowledge once and instantly reuse it for investor updates, pitches, and product planning.
Agencies
Juggling multiple clients means constant context switching and data-leak anxiety. Keep each client's context isolated, clean, and ready to reuse - no cross-contamination.
Limited Beta
Your Context. Under Control.
Mesh is in limited beta. Early members get free access and a tool that
makes context control effortless.
How long does it take to get up and running with Mesh?
Most users have their first context stack built within 10 minutes of installation. You connect your Notion workspace using your API key, point Mesh at your local folders, and start adding items to your Stack. There's no configuration file to edit, no CLI to learn, and no pipeline to set up. If you've ever used a file manager, you already know how to use Mesh.
Which AI tools and LLMs does Mesh work with?
All of them. Mesh is completely model-agnostic. It compiles your context into a clean, formatted payload that you copy to your clipboard or export directly. That means it works with ChatGPT, Claude, Gemini, Grok, your IDE's AI assistant (Cursor, Copilot, Windsurf), or any custom API workflow you've built. If it accepts a text prompt, Mesh feeds it.
I already have a system for this: copy-paste, Notion templates, etc. Why switch?
Those systems work until they don't. The moment you're pulling from three sources, tracking token limits, and worrying about accidentally including an API key in your prompt, the manual approach starts costing you more time than it saves. Mesh handles the assembly, the token counting, and the privacy scanning automatically. Your "system" becomes a single click instead of a 5-minute ritual before every serious prompt.
What exactly is a Just-In-Time (JIT) context engine?
It means Mesh pulls the live, current version of your documents at the moment you build your Stack - not a cached or manually updated snapshot. When you add a Notion page to your Stack, Mesh fetches it fresh. When you include a local file, it reads the latest saved version. Your AI always gets the most up-to-date context, without you having to remember to re-copy anything.
How does token management work, and why does it matter?
Every LLM has a hard limit on how much text it can process at once. If you exceed it, the API either rejects your request or silently cuts off your content. This means incomplete, unreliable outputs. Mesh shows you a real-time, model-aware token count as you build your Stack, so you can trim and optimise before you send. You choose the target model, and Mesh tells you exactly where you stand.
Does Mesh store or transmit my files and documents?
No. Mesh runs entirely on your local machine. Your Notion content, local files, and assembled context are never sent to HiveTrail's servers. The Privacy Scanner, which detects API keys, PII, and internal paths, also runs locally, so sensitive data is caught and replaced before it ever leaves your device. The only outbound connection Mesh makes is to fetch your Notion content directly from Notion's API, under your own credentials.
What platforms does Mesh run on?
Mesh is currently available for Windows, with Linux coming out shortly. A MacOS version is in active development and will be available to beta users first. If MacOS support is important to you, joining the waitlist now puts you at the front of the queue.
