Opportunities › Scheduling and orchestration for AI agents › Proposed app
Tickrun
Hosted control room for scheduled AI agent routines, with run history and alerts
- Score
- 50
- confidence 43
- Evidence
- 4
- items on the page
- Rivals
- 1
- named in sources
- First version
- 35 d
- estimate
- Type
- Desktop app
- PWA: runs in the browser, installs on Mac and Windows
- Market since
- 2025
- New market · AI estimate
ScreensConcept
Desktop app: Developers monitor scheduled runs, check failure alerts, and review agent output in a persistent control room dashboard. Sample screens on a computer, in the proposed brand. Their numbers are sample data.
Routines
1 needs attention12 active
About this appAI proposal
Tickrun is a hosted dashboard for the recurring jobs your AI agents run. Connect a git repository of routine files, and Tickrun shows what is scheduled, what ran, what failed and what each run produced, across the agents and machines you use. It is for developers and small ops teams who run agents on their own laptops, servers or CI and have outgrown cron lines and custom scripts. Small runners on your machines do the work; your code and keys stay with you.
Routines stay as plain files in git, so changes are reviewed and reversible. Tickrun is not tied to one agent: a routine names a command and an agent type. The dashboard is a phone-friendly PWA, so you can pause a routine or read a failure from anywhere.
- Tagline
- Know what your agents did while you were away.
- Voice
- PlainCalmPrecise
- Why this name
- A tick is one beat of a schedule, and a run is one job. Two short plain words joined, easy to say and spell.
In the first version
Members say which features they would use. It tells PWAS what people want; it changes no score.
Git-backed routines
Routines are files in your repo. Pushes sync automatically, with a diff of what changed in the schedule and who changed it.
No member yet
Any agent, any machine
Each routine names an agent command and a target runner. Mix different agents on Mac, Linux and Windows hosts.
No member yet
Run history and output
See every run with start time, duration, exit status and captured output, searchable across all routines.
No member yet
Failure alerts
Get an email when a routine fails, is skipped or runs far longer than usual. Mute or pause from your phone.
No member yet
Brand identityAI proposal
Check the name against trademark registers before using it.
Palette
#0F4C4ADeep Teal · primary#F6F3ECPaper · surface#1B2422Ink · text#E8A33DAmber · accent#C0392BSignal Red · error / failed runs#5E8C61Moss · success / data
Typography
Aa
Tickrun
PricingAI proposal
The material gives no competitor prices; it describes one open-source scheduler with no pricing shown. These tiers are a starting point to test, not derived from market data.
Free
Free
- 1 runner
- 3 routines
- 7 days of run history
- Email alerts
Pro
$12 a month
- 5 runners
- Unlimited routines
- 90 days of run history
- HTTP and MCP triggers
Team
$39 a month
- 20 runners
- Up to 10 members with roles
- 1 year of run history
- Priority support
Would you pay Pro · $12 a month?
Your answer tells PWAS which prices people accept. It changes no score.
No answers yet.
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
$194,000
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
- Users invite others. A team owner invites teammates and on-call people to view runs and pause routines. Alert emails and shared run links point to the dashboard for colleagues who do not yet have accounts.
- Do they become customers?
- Invited teammates are developers who can become paying team members. Test whether invitees create their own free accounts and whether a second person on a team triggers an upgrade.
- First customers
- Solo developers and teams of two to ten engineers who already run recurring coding or reporting agents on their own machines or CI.
- Where to reach them
- Hacker News and developer forums: Post a write-up on monitoring scheduled agent runs, with a free tier link, in threads about agent scheduling.
- Open-source agent communities: Offer a documented routine file format and import for common agent setups, announced in project discussions.
- First milestone
- Fifty free signups with a connected runner and five paying Pro or Team accounts within eight weeks.
Why people already pay for this
- VerifiedHacker News post received 37 points and 19 comments
- Public claimThere is significant adoption and daily usage of agent scheduling solutions
- AI inferenceUsers need agent scheduling that supports multiple agent types without lock-in
- Public claimExisting solutions lack open-source, git-compatible, agent-agnostic scheduling
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 · Runner agentSmall cross-platform binary that polls for jobsExecutes routines on the user's own machines so code and keys stay local.
- This app · Git syncGit host webhooks and read-only deploy keysReads routine files from the user's repo and syncs on push.
RisksAI inference
- CommercialAn open-source local daemon already exists with reported daily users. Developers may see no need to pay for a hosted dashboard on top of it. Willingness to pay must be tested.
- TechnicalRunners on varied operating systems behind firewalls or asleep laptops make reliable scheduling and status reporting hard.
- DataRun output can contain secrets or private code. Storing it needs redaction options and clear retention controls.
- PlatformAgent tools change command-line behaviour often, so routine definitions may break between versions.
- CommercialEvidence is a single post with 37 points and 19 comments; demand beyond hobbyists is unproven.
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.