killBottleneck

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🧪 Public beta. killBottleneck is feature-complete and in beta — the cloud and the self-hosted version alike; it is one and the same app. What we are testing here is the self-hosted side: installation, reverse proxies, your own SMTP, upgrades. Install it (Quick start below), try to break it, and tell us what happened: bugs → Issues, ideas → Discussions. v1.0 ships when the beta goes quiet.

A visual picture of your projects, your company and its processes — goal maps that people and AI agents work on together, entirely on your own server: your data never leaves the company. Open in the spirit of open source, just without the right to resell it as a hosted service — see License.

Nothing here phones home. On a default install the server sends no request anywhere, and the app loads nothing from a third-party CDN — fonts included, they are served from your own instance. Everything that could leave your network is something you switch on:

There is no telemetry, no analytics and no licence check.

Quick start

All you need is Docker. Then:

cp .env.example .env    # optional — the defaults are fine
docker compose up -d

killBottleneck runs at http://SERVER-IP:8090. Colleagues on the local network just open it in a browser.

The first user to register automatically becomes the administrator. Everyone else can register themselves, or the administrator invites them from Administration (this creates an account with a temporary password to hand over).

What it does without AI

A full goal map editor (nodes, edges, statuses, notes), multiple maps per user, comments on goals, sharing maps with colleagues (read / edit), public maps, export to image/PDF.

The “My day” panel (both the home page and the Tasks page): a clickable overview of overdue / today / within a week / blocking others, computed live from your data; name days next to the date; a portrait PNG export for mobile — both full (with task names) and anonymous (names redacted, for social media). Over HTTPS you also get Share… (your phone's native Web Share dialog, no third-party service involved).

Time tracking: a ⏱ timer in the top bar (one click starts an “empty” measurement — the project/client/goal is assigned while it runs or afterwards), a timer on every task and every goal in a map (measuring never changes a status — it is purely supplementary), a left-hand “Time tracking” panel with the records (from–to, retroactive assignment), a “Time worked” dialog in the user menu (today/this week, broken down by project and client), a client registry (project→client, so time adds up per client too), and auto-stop for forgotten timers after 12 h. Inbox behaviour: an unassigned measurement stopped with a note (e.g. “call with the client”) also saves itself as an idea in your stash.

On a phone

The same instance, opened on a phone, switches to a simplified view: today's tasks, tick them off, add one, and read messages — no map canvas to fight with on a small screen. You can switch back to the full view at any time, and the app can be added to the home screen (over HTTPS) so it behaves like a native one.

More in the Simplified view guide.

AI features (optional)

The assistant lives in a side panel next to your maps. It plans your day with you (morning briefing, evening planning), sorts notes from a photo, a PDF or a voice note, drafts a whole project after a few questions, prepares a meeting, reviews your week and, for managers, runs a team meeting. It reads your maps itself; every change it proposes is a card you confirm — nothing is written behind your back. E-mails, notes and summaries it writes are kept as documents next to the chat. Besides the assistant there is the wand on a node (sub-steps, milestones, KPIs, risks), an AI project summary and the daily encouragement in My day.

AI is switched on in .env via KB_AI_PROVIDER:

• openai — any OpenAI-compatible API: OpenAI, OpenRouter, Groq, Mistral, Together, or your own vLLM / LM Studio / llama.cpp / liteLLM proxy. Set KB_AI_URL=https://openrouter.ai/api/v1 (the base address, usually ending in /v1), KB_AI_TOKEN=<your API key> and KB_AI_MODEL=<exact model name>. Voice notes are transcribed by the same service when it offers a Whisper / transcribe model; your provider bills you for the requests.
• api — a remote AI service compatible with the killBottleneck API contract: enter the address and token you got from your provider. No GPU of your own and no maintenance. (Runs the wand, the summary and the encouragement; the assistant needs ollama or openai.)
• ollama — your own local model: install Ollama, pull a model (ollama pull gpt-oss:20b) and set KB_AI_URL=http://IP:11434 + KB_AI_MODEL=gpt-oss:20b. Everything runs on your side, no data leaves your network. (Voice notes need a speech-to-text service of your own — see below.)
• custom — your own endpoint honouring the same API contract (the contract is written down here).

The assistant uses the same model unless you give it its own (KB_CHAT_PROVIDER/URL/MODEL/TOKEN). Reading photos needs a vision model (KB_VISION_*, or tick The assistant reads images in Administration → AI). Voice notes work with any speech-to-text in the OpenAI shape (KB_TRANSCRIBE_PROVIDER=openai + KB_TRANSCRIBE_URL — speaches, whisper.cpp, OpenAI…); the recording itself is never stored. Browsers allow the microphone only over HTTPS (or localhost), and a reverse proxy in front must let request bodies of about 5 MB through (a voice note or a photo travels inside the request). More in the assistant guide.

When AI is used, map data is sent to the endpoint you chose; with none (the default) nothing ever leaves your server.

Daily AI encouragement (a line in the My day panel): 1–2 sentences prioritising “what blocks others → overdue → today”, with the occasional proverb. It is generated in the morning by a cron job (KB_SUMMARY_HOUR, default 6) only for accounts that signed in within the last KB_SUMMARY_ACTIVE_DAYS days (default 14, 0 = everyone); for the rest it is generated when they open the app. Optionally a separate (smaller/faster) model just for the summaries: KB_SUMMARY_PROVIDER/URL/MODEL/TOKEN — without them the general AI configuration above is used. The panel works in full without AI, just without this one line. The AI never enumerates task lists (those are computed from your data and clickable) and task names are sanitised before they go into the prompt.

AI assistant over MCP (Claude Desktop, Claude Code, …)

killBottleneck ships with a built-in MCP server (mcp/): connect your AI assistant to your own instance and maps get built conversationally — “make a map out of these meeting notes”, bulk edits, ticking off what's done. It works the same for self-hosted and hosted instances, only the address differs.

1. In the app: user menu → API keys → a new key with the Read and write scope (Read only is enough for read access). The token is shown only once. Recommended: give the key an expiry and revoke it once you stop using it.

2. Nothing to install — the server is on npm as killbottleneck-mcp, so npx fetches it on first use. (Prefer running it from this repository? cd mcp && npm install and use node /absolute/path/mcp/index.js instead of the npx command below.)

3. Register it with your assistant:

   Claude Code:

   bash

   claude mcp add killbottleneck \
     -e KB_URL=http://SERVER-IP:8090 \
     -e KB_API_KEY=kb_user_... \
     -- npx -y killbottleneck-mcp
   

   Claude Desktop (claude_desktop_config.json → mcpServers):

   json

   {
     "mcpServers": {
       "killbottleneck": {
         "command": "npx",
         "args": ["-y", "killbottleneck-mcp"],
         "env": {
           "KB_URL": "http://SERVER-IP:8090",
           "KB_API_KEY": "kb_user_..."
         }
       }
     }
   }
   

Tools (20): list_maps, get_map, create_map, add_nodes, update_node, delete_node, list_people, get_portfolio, get_org_structure, calendar events and timed reminders (create_event, list_events, create_reminder) and the rule tools (create_rule, list_rules, update_rule, delete_rule, list_rule_runs, list_rule_templates, save_rule_template, delete_rule_template). A goal with an assignee or a deadline IS a task — there are no separate task records. Assigning an owner through the API shares the map with that person as a collaborator, so the work shows up in their My Day (the response lists who was shared with).

Remote, without anything local: every instance also serves MCP directly at /mcp (Streamable HTTP, same keys, same tools) — claude mcp add --transport http killbottleneck https://your-instance/mcp --header "Authorization: Bearer kb_user_..."; the claude.ai connector signs in through OAuth. Details: MCP server.

Security: a key acts as its owner — it sees and edits exactly what the owner can in the app, shared and team maps included (edit/own = full write; work and read = only the status of the owner's own nodes, exactly like ticking off in the app); it never reads the account's role, so an admin's key cannot see anyone's private map, and someone else's public map is not reachable either (404). Administration, AI settings and users are never reachable. Writes can add/edit/delete goals and tasks; a whole map cannot be deleted through the API, and neither can the apex of a map. Limits: 120 reads + 30 writes per minute per key, at most 200 nodes per call, at most 20 keys per account. Working alongside an open editor is handled by conflict detection (the editor offers to reload, the assistant reloads the map itself). Note: add_nodes re-runs the layout of the whole map. MCP tool output is in English (assistants always understand it); server error messages arrive in the language of your account.

Who performs a step: a person, or an automation

For every goal in a map you can say whether a person or an automation does it. Whether there is an AI agent or a scheduled cron job behind that automation is not your problem — whoever builds it knows.

Important: the responsible person for a goal is always a human. Even for an automated step there is someone accountable, who gets the notifications and whose “My day” the goal counts towards. The automation does the work; a person is answerable for it.

For an automated step you also record which automation does it — this is a record of how things are today (“n8n already does this step for us”), not a command. That is what makes it visible at a glance which parts of the map are done by people and which by machines.

“I would like this automated”

On any goal you can tick a request to have the step automated, and optionally add a sentence explaining why. The request goes to the AI agent manager — a separate flag on a user (User management → AI manager), independent of their role; both an administrator and an ordinary member can hold it alongside their role.

Once the manager builds the automation and records it on the goal, the request tidies itself away and the requester gets a message that their goal is now automated. The full cycle:

person: ☑ I would like this automated  ("I upload subtitles by hand, 20 minutes")
   ↓
the AI manager gets a notification → decides → builds an n8n workflow
   ↓
the manager records it on the goal: "n8n — subtitle translation"
   ↓
the requester gets a notification: "your goal is now automated by n8n — subtitle translation"

Attachments on a goal

You can upload files to any goal. On a goal with an automation, uploading a file starts it right away — instead of filling in a form somewhere else you simply attach whatever needs processing (typically subtitles, source material, an export).

Attachments are visible only to people with access to the project. The files are protected: the link alone gives nothing away.

AI agent registry

The AI agent manager (or an administrator) maintains a directory of automations under AI agent registry: name, webhook address, signing secret, enabled/disabled. On a goal the automation is picked by name — team members never see the address or the secret. When the name on a goal matches an agent in the registry, killBottleneck can start it itself.

Who may start it. Each agent can carry a list of allowed e-mail addresses. An empty list means the automation can be started by anyone who can edit any map — inside a company that is usually fine, but restrict it on an instance you let contractors into: whoever may edit a map can otherwise start any of your n8n workflows and feed their own text into it (the goal's title and description go to the agent in the payload).

Attachments are capped at 200 files per project, plus an optional space limit for the WHOLE instance (KB_FILES_MB in MB; 0 = uploads disabled entirely, empty = no limit — set one on a shared disk so a hosted instance cannot fill it up). ⚠️ The former FLOWMAP_MAP_FILES_MB was a PER-PROJECT quota defaulting to 200 MB — if you have it set it still applies to you, but without it there is now NO space limit at all.

An automated run: killBottleneck → n8n → back

An automation starts when:

• an attachment is uploaded to the goal, or
• the goal's turn comes — it was waiting for its sub-goals and they have all just been completed, or
• somebody manually switches the goal to “in progress” (this is also how you retry a failed run)

A running automation will not be started a second time until it reports back or expires.

The outgoing request (POST to the agent's address, with an X-Signature header = HMAC-SHA256 of the entire body using the agent's secret):

{
  "run_id": "…", "run_token": "kbr_…",
  "callback_url": "https://your-instance/api/kb/agent-callback",
  "files_url": "https://your-instance/api/kb/agent-files?run_token=kbr_…",
  "files": [{ "id": "…", "name": "subtitles.sbv", "size": 1234, "url": "https://…?run_token=kbr_…" }],
  "map_id": "…", "map_title": "…",
  "node_id": "…", "node_title": "…",
  "description": "…", "deadline": "2026-08-01",
  "owner": "responsible@company.com", "triggered_by": "who@company.com"
}

The agent downloads files using its run token; files_url is a live listing, so it also sees attachments added while it is running. The token expires once the result is reported.

Reporting back (POST to callback_url, no login — the run token authenticates it):

{ "run_id": "…", "run_token": "kbr_…", "status": "done", "result": "Translated into 3 languages" }

status is done or failed. A token is valid for one goal and one report — a second call with the same token will not go through.

After done the goal is completed, and that sets the rest of the process in motion: the following goal is unblocked and the person responsible for it is notified that they can start. If that following goal is automated as well, it starts straight away — so the steps chain themselves.

Set the address the agent should call back on. callback_url is assembled by the server, not the browser — without configuration it uses PocketBase's “Application URL”, which after installation is http://localhost:8090. An agent running on another machine would therefore call itself, and the run would hang until it timed out. In .env:

KB_PUBLIC_URL=https://killbottleneck.yourcompany.com
KB_AGENT_TIMEOUT_MIN=90

Any address the agent can reach will do — on a self-hosted setup http://192.168.1.10:8090 on the LAN is perfectly fine. Hosted instances (killBottleneck Cloud) have this set automatically.

Is your n8n on the same network? The webhook address is called by the server, which makes it a classic internal-network scanning vector — so by default killBottleneck refuses to call private addresses (10.x, 192.168.x, 172.16–31.x, localhost, cloud metadata). On a self-hosted setup where n8n runs next to killBottleneck, allow it:

KB_ALLOW_PRIVATE_WEBHOOKS=1

Without this the run is marked failed and the AI agent manager gets a message explaining why. An agent must have its secret filled in — without one the request would be signed with an empty key and the recipient would have no protection whatsoever, so killBottleneck rejects such a run outright. The currently effective address is always shown at the bottom of the AI agent registry, which warns you when it points at localhost. This only concerns automations — if you do not use them, you do not need to set this variable.

When an automation does not finish

The state of a run is visible right in the goal's dialog — pending / running / done / failed, with the reason on failure. A run is restarted by switching the goal back to “In progress”.

What each state means:

A run that does not report back within KB_AGENT_TIMEOUT_MIN (default 90) minutes is marked failed by a watchdog, which notifies both the responsible person and the AI agent managers — so a goal never hangs silently.

The most common causes of failure: the agent is not in the registry or is disabled; it has no secret; its address points into a private network and KB_ALLOW_PRIVATE_WEBHOOKS=1 is missing; or the webhook is unreachable. The details (including connection errors) are in the server log — docker compose logs killbottleneck — they are deliberately not surfaced in the app.

Moving a project elsewhere (JSON export and import)

A project can be exported to a .json file and imported somewhere else — between colleagues and between instances. In the editor: Export → Export JSON, choosing with names or without names. Import lives in the menu next to the “New project” button.

What the file contains: the title, the description, the whole goal structure (including statuses, deadlines, who performs each step and automation requests) and the tasks attached to it. The “without names” option clears both the responsible people and the assignees — the names of automations stay, since they describe the process.

Switching from Asana or Trello: the same import also accepts an Asana project export (CSV) and a Trello board export (JSON). Sections/lists become map branches, tasks/cards become goals, subtasks and checklists become child goals; statuses (done), due dates, descriptions and — for Asana — assignees carry over (e-mails unknown to this instance are cleared and counted). Everything is converted locally in the browser — nothing calls Asana or Trello. Limit: 400 items per file.

What is not transferred: attachments, comments, sharing, archiving and numbering series. An import always creates a new project owned by whoever imports it, regenerates the goal identifiers (so it does not collide with the original) and shares nothing with anybody and sends no notifications — you have to share the project manually to collaborate on it. Assignments to e-mail addresses that do not exist on this instance are dropped, and the import tells you how many.

Appearance (skins)

In the avatar menu → Appearance everyone picks one of twelve built-in skins — Indigo (default), High contrast, Terminal, Paper, Ocean, Forest, Midnight, Plum, Peach, Graphite, Ruby or Rose. The choice is saved to the account, so it applies on every device, in both light and dark mode, and in the simplified lite view too (the picker there sits in the footer).

Custom skins: a skin is a small JSON file (kb-skin v1 format) — a set of colors (HSL), fonts and corner radius. The Appearance dialog can export the current skin (for a built-in, its definition — "take it and tweak it") and import someone else's, from a file or by pasting. By design it is not arbitrary CSS: values pass a whitelist on both the client and the server, so a shared skin cannot run or send anything. No web fonts are ever downloaded — only fonts bundled with the app and system fonts are used; an unknown font harmlessly falls back to the next one in the stack.

Company look: an administrator sets the instance-wide default skin in the organization admin — it applies to everyone who has not picked their own, including the login screen. A user's own choice always takes precedence.

What a skin does not change in v1 (by design): status colors (red/amber/green = overdue/in progress/done stay readable everywhere the same). Map export (PNG/PDF) is true to the screen — captured in the active skin and light/dark mode, including the background color; only the backdrop artwork is left out. The project dashboard PDF and the "My day" image deliberately stay light so they can be sent to anyone.

Community skins and the open source skin editor: https://github.com/tengolabs/killbottleneck-skins — skins are free data (CC0), the editor is MIT. Try the editor right in your browser, nothing to install: https://tengolabs.github.io/killbottleneck-skins/.

Notifications

The bell in the header shows the last 20 events; the full list with filters and paging is at /notifications. That is also where notification settings live, so everyone can switch individual types on or off.

Notifications are sent for: a task or a goal being assigned to you (including in a map that already exists), a comment on a task or a goal, a project being shared with you, a waiting goal being unblocked, an approaching or missed deadline (one digest per day, not one per item), an automation request and its fulfilment, an automation finishing or failing, and a timer being stopped automatically.

Deadline reminders are sent in the morning; set the hour with KB_DEADLINE_HOUR (default 7, the container's local time). Notifications you have read are cleaned up after 30 days.

The e-mail channel is ready but only switches on once SMTP is configured (see below) — until then it is greyed out in the settings.

Time zone and recurring templates

A template can be set up so that a project is created from it automatically (e.g. “every Monday” or “on the Nth day of the month”). For “Monday” and the time of creation to match your local time, set this in .env:

TZ=Europe/Prague     # your time zone (empty = UTC)
KB_AUTO_HOUR=5  # the hour (0–23) from which projects are created on a given day

• If the server slept through that hour (it was switched off), the project is created at the next later hour of the same day — it is not skipped.
• The zone applies to the whole instance — for a team spread across zones the server's zone is used, not each user's.
• Recurring tasks (moving the deadline on completion) deliberately compute in UTC, so crossing midnight or a daylight-saving change does not shift them by a day.

Data and backup

All data lives in the ./pb_data folder (SQLite + uploaded files). Use the bundled script to back it up:

./backup.sh                 # creates kb-backup-YYYY-MM-DD.tgz
./backup.sh restore FILE    # restores data from a backup

(By hand: to back up, copy the pb_data folder; to restore, put it back.)

Backups can be encrypted: set KB_BACKUP_PASSPHRASE and the script writes kb-backup-….tgz.gpg (GPG, AES-256). restore accepts encrypted as well as older plain archives. Keep the passphrase off the server — without it nobody can read the backup.

Taking all your data with you

My account has Download all my data: one JSON file (killbottleneck.export/1) with every project you can see — each in the same shape as a single map export, so it imports elsewhere — plus tasks, rules, comments, change log, attachment list, idea stash, time entries, external contacts and notifications. It works even after a trial has expired, and Upload data from an export brings the projects (with rules) and the idea stash back into another instance. Self-hosters additionally have ./backup.sh, which backs up the whole pb_data folder including uploaded files.

Team

One instance = one team. Roles: Administrator (manages users and roles, organization settings — name and logo), Manager (invites members, sees and manages all tasks), Member (their own tasks and shared maps). Administrators and managers also get Organization in the top bar — the view from above across team and shared projects (private projects are never counted). You can invite people from Administration or straight from the Tasks page.

Registration and the registration key

The first account to register becomes the administrator. If the instance is reachable from the internet, set KB_SETUP_CODE in .env — every registration then requires that key, so not just anyone who knows the address can create an account. Hand the key out to the people you want to let in; on top of that an administrator can invite users directly (an invitation does not need the key). Empty = registration without a key.

Sign in with Google (optional)

Users can sign in with Google instead of e-mail and password. To set it up:

1. In the Google Cloud Console go to APIs & Services → Credentials → Create credentials → OAuth client ID → type Web application.
2. Under Authorized redirect URIs add: https://YOUR-DOMAIN/api/oauth2-redirect
3. Copy the Client ID and Client secret into .env:
   code

   KB_GOOGLE_CLIENT_ID=…apps.googleusercontent.com
   KB_GOOGLE_CLIENT_SECRET=…
   

4. docker compose up -d — the “Sign in with Google” button appears by itself.

Empty variables = Google sign-in is off (the button is not shown). On an instance with a registration key, Google sign-in is only for existing users — a new account cannot be created through Google (there is no way to enter the key), so the account has to be created with the key first.

Attachments on goals: a file, or a link

You can pin either an uploaded file or a link (Drive, OneDrive, SharePoint, a specific e-mail, anything on https://) to any goal. A link has three advantages: it takes up no space, the team always opens the current version, and the file stays where you keep it.

How much space uploaded files may take is governed by KB_FILES_MB — it applies to the whole instance, not per project:

Hosted instances run with 0: that way the provider does not hold your documents, only links to them. A link has to start with http:// or https:// — a network drive path (\\server\folder) will not open from a browser for security reasons, so that belongs in the description.

E-mail (SMTP, optional)

SMTP is configured in the PocketBase admin UI: http://SERVER-IP:8090/_/ → Settings → Mail settings (the superuser account is created on first start — you will find the link in docker compose logs). With SMTP configured:

• an invitation to a new user is sent by e-mail (with a link to set a password) — without SMTP the administrator is shown a temporary password to hand over manually,
• self-service password reset works.

HTTPS (access from outside)

killBottleneck itself runs over HTTP — to reach it from outside your LAN, use a VPN or a reverse proxy. An example with Caddy (automatic HTTPS certificates):

# Caddyfile
killbottleneck.your-domain.com {
    reverse_proxy 127.0.0.1:8090
}

Add it to compose through docker-compose.override.yml (that file is not overwritten by updates):

services:
  caddy:
    image: caddy:2
    ports: ["80:80", "443:443"]
    volumes:
      - ./Caddyfile:/etc/caddy/Caddyfile
      - caddy_data:/data
volumes:
  caddy_data:

HTTPS additionally unlocks Share… for the “My day” image (the Web Share API — your phone's native share dialog, no third-party service) and adding the app to your phone's home screen (a service worker only runs in a secure context). Browsers do not allow either of these over plain HTTP; on an HTTPS domain they appear by themselves, with no configuration.

Turn on compression in your proxy — it is a threefold saving

killBottleneck does not compress responses itself (there is no way to enable it safely in PocketBase without breaking how the API behaves when it rejects an oversized body). The main frontend file is 488 kB uncompressed and 157 kB gzipped — on mobile data that is the difference you notice most when opening it for the first time. One line is enough:

# Caddyfile
killbottleneck.your-domain.com {
    encode gzip zstd
    reverse_proxy 127.0.0.1:8090
}

(In nginx: gzip on; gzip_types application/javascript text/css;. Behind Cloudflare or a similar service it happens on its own — there is nothing to configure.)

Updating

git pull            # or download the new version
docker compose up -d --build

Database migrations run automatically on start. Before a bigger update it is worth taking a backup (./backup.sh).

Always with --build: the app and its server-side logic are baked into the image, so after every update (a code change, .env variables such as TZ) you need docker compose up -d --build, not just restart.

One-off, when updating from a version up to v0.11: after the product was renamed the container is called killbottleneck instead of flowmap. The old container holds port 8090, so the new one would not come up — stop and remove it first:

docker rm -f flowmap
docker compose up -d --build

Your data is in the ./pb_data folder on disk, not in the container — you will not lose anything. FLOWMAP_* variables in your .env keep working, there is no need to rewrite them.

Notes

• A public link to a map shares only the map canvas — tasks and task comments are not visible through it.
• Licence: fair-code — Sustainable Use License (see the License section below).

License — fair-code

killBottleneck isn't "open source" in the strict (OSI) sense — and we say so plainly. It's fair-code: the source is public, you can download it, run it, modify it and use it, and for the vast majority of people it delivers the same benefits as classic open source. The parts that can be classic open source, are: the skin editor (MIT) and the whole skin gallery including its validator (CC0).

You get the whole of killBottleneck — every feature, including team collaboration and the AI features. No stripped-down "free version", nothing locked behind a paywall. You can even power the AI yourself, for free — with your own model (Ollama) on your machine, or your own API key. Our hosted cloud (AI included) is offered only as a convenience for those who have nowhere to run killBottleneck — it's convenience, not a condition.

What you may do with killBottleneck — free and with no catch:

• Run it yourself on your own computer or server — your data stays with you.
• Use it in your company for your own work and your team — fully.
• Plug in your own AI (a local model or your own API key), or use no AI at all.
• Modify it however you need.
• Offer services around killBottleneck (setup, consulting, customizations for a client).

What we keep for ourselves — and what keeps killBottleneck alive:

• Hosting killBottleneck and charging people for access.
• White-labeling it — releasing it under someone else's brand.
• Reselling it as a paid service.

That's our business — it's what lets us keep adding features, fixing bugs, and keeping killBottleneck alive. We actively encourage you to build on killBottleneck and use it however you need; just don't turn it into a competing hosted service. Full terms: LICENSE. Third-party components keep their original licenses (MIT, Apache-2.0, BSD, …) — the full list with license texts is in THIRD-PARTY-LICENSES.md.

Rights holder: Tengo, s.r.o., ID No. 03339165, Dolní Valy 205, 262 72 Březnice, Czech Republic. Want to host killBottleneck as a service, ship it under your own brand, or resell it? The license doesn't allow that — but a commercial license is available, write to licence@killbottleneck.com.

Česká verze této sekce je v README.cs.md.

Built by Richard Pobrislo (LinkedIn, Ctrl+Alt+AI) — one person, which is why the support channels below are what they are.

The code is written 100% by AI — Claude Fable 5, Claude Opus 5 and Claude Opus 4.8 — under human direction. Every release goes through an automated regression suite and a manual click-through before it ships; the release notes list what was verified and what deliberately wasn't.

Contact

We do not accept code from outside contributors (see CONTRIBUTING.md) — ideas and bug reports we do, and they are welcome.

Supporting the project

killBottleneck is fair-code — the whole product (every feature) is free to self-host and will stay that way. If it helps you:

• follow our YouTube channel with tutorials and AI news,
• join us on Discord.