Opportunities › Multi-machine access for AI agents and developers › Proposed app
Benchwork
One place to reach agent sessions, files and logs on every machine you run
- Score
- 48
- confidence 46
- Evidence
- 3
- items on the page
- Rivals
- 3
- named in sources
- First version
- 60 d
- estimate
- Type
- Desktop app
- PWA: runs in the browser, installs on Mac and Windows
- Market since
- 1995
- Mature market · AI estimate
ScreensConcept
Desktop app: Engineers monitor and control remote machines, agent sessions and logs from their workstations, reviewing files and dashboards during extended development sessions. Sample screens on a computer, in the proposed brand. Their numbers are sample data.
Machines
1 needs attention5 online
About this appAI proposal
Benchwork puts your Mac, Linux and Windows machines on one screen. Open an agent session, browse files, read logs or take over a desktop without juggling SSH windows, remote desktop apps and scripts.
It also runs an MCP server, so your AI agents get the same reach you do: read a file on the build box, tail a log on a server, or start a session on a laptop, with every action recorded and permissioned per machine.
Run it yourself on your own hardware, or use the hosted version. Your machines stay under your control, and you are not tied to one vendor's network layer. It works on top of a private network you already use.
- Tagline
- Every machine within reach, for you and your agents.
- Voice
- PlainSteadyPractical
- Why this name
- A bench is where you keep your tools laid out and within reach. Benchwork is the steady daily work of tending many machines from one place.
In the first version
Members say which features they would use. It tells PWAS what people want; it changes no score.
One list of every machine
See Mac, Linux and Windows machines together with online state, running agent sessions and recent activity.
No member yet
Agent sessions in one view
Start, watch and stop agent sessions on any machine, and jump between them without opening another terminal.
No member yet
Files across machines
Browse, preview and copy files between machines from the browser, with no manual scp or shared drive setup.
No member yet
Merged log stream
Follow logs from several machines in one time-ordered feed. Filter by machine, session or text.
No member yet
Brand identityAI proposal
Check the name against trademark registers before using it.
Palette
#2F5D50Pine · primary#F6F1E7Paper · surface#1F2A24Ink · text#D9822BCopper · accent#3B6EA5Slate blue · data
Typography
Aa
Benchwork
ABCDEFGHIJKLMNOPQRSTUVWXYZ 0123456789
Every machine within reach, for you and your agents.
PricingAI proposal
Tailscale's verified pricing page shows a free plan, paid plans from $1 to $18 a month, and quotes on request for larger customers. These tiers sit in that range as a starting point to test.
Self-hosted
Free
- Run on your own hardware
- Machines, sessions, files, logs
- MCP server with scoped access
- Community support
Solo hosted
$5 a month
- Hosted server, no setup
- Up to 5 machines
- 30 days of log history
- GitHub link per session
Team
$15 a month
- Per user, shared machines
- Agent permissions per machine
- Audit trail of agent actions
What it could be worthEstimate
What a software business making this much sells for today, from real deals. Pick a monthly revenue.
If it makes
Worth about
$190,000
Sale range $132,000 to $263,000
$120,000 a year in revenue
From 87 software businesses listed and sold on Empire Flippers in the last year, revenue vetted by the broker: they sell for about 19× their monthly revenue, most between 13× and 26×.
Measured on profit, the middle deal is 32× monthly net profit: about 2.7 years of profit.
An estimate, not an offer or financial advice. A real price depends on profit, growth, churn, how much of the work is the owner's, and the buyer.
How it would growAI proposal
How the product would reach new customers through its own use, and how the first ones would be found. A plan to test, not a result.
- Built-in loop
- Partners and integrations. List the MCP server in MCP directories and agent tool docs, and publish setup guides for common agent tools. Agents and their users find Benchwork where they pick tools.
- Do they become customers?
- People who find it through agent tools are developers who can pay or move their team to it. Test whether solo users upgrade to Team, and whether a self-hosted user brings a paying teammate.
- First customers
- Small teams of 2 to 10 AI engineers who run coding agents on a mix of Mac, Linux and Windows machines, such as a laptop, a build server and a GPU box.
- Where to reach them
- GitHub and open-source release: Release the self-hosted core, then write up setup for common agent workflows. Offer hosted for people who want no setup.
- MCP and agent communities: Post demos of agents working across machines in forums and Discords for agent builders.
- Developer newsletters: Pitch a short case study on running agents across several machines from one place.
- First milestone
- Ten teams paying for the Team tier after a 30-day trial, from at least two different agent communities.
Why people already pay for this
- VerifiedGitHub repository gained 376 stars in 19 days
- Public claimUnified access to agent sessions, desktops, files, logs and GitHub across multiple operating systems with MCP server integration
- VerifiedTailscale's pricing page lists 4 paid plans, from $1 to $18 a month, plus a free plan and prices on request for larger customers
Tech stack
Every proposal builds on the same PWA base, installable from the browser on any phone or computer. Dashed boxes are what this app adds.
- AppNext.js and TypeScript
- PWAManifest and service worker
- UITailwind CSS
- Data and authSupabase Postgres
- PaymentsStripe
- EmailResend
- HostingVercel
- This app · Machine agentSmall cross-platform daemon for Mac, Linux, WindowsEach machine needs a local helper to run sessions, serve files and ship logs to the server.
- This app · Realtime transportWebSocket relay with end-to-end encrypted streamsLive terminals, logs and desktop need low-latency two-way channels beyond plain requests.
RisksAI inference
- TechnicalA reliable agent on Mac, Linux and Windows, with live terminals and browser desktop, is a lot to build and support. Windows desktop and NAT traversal are likely the hardest parts.
- CommercialDevelopers may prefer free open-source tools plus a private network they already use. Willingness to pay for a hosted layer is unproven.
- RegulatoryGiving agents access to files and logs may expose secrets or personal data. Teams will ask for audit trails and compliance features before adopting.
- AIAn agent with machine access can delete files or run harmful commands. Weak default permissions would damage trust quickly.
- PlatformMCP is a young standard and may change. Mac and Windows may also restrict screen capture and background services.
Everything marked AI proposal or AI inference was written by a model from the evidence on the opportunity page. The proposed name must be checked against trademark registers before it is used.