The Signallloom Developer Toolkit turns every AI feature you build into a revenue stream — not a cost center. Route AI traffic, earn passively, refer clients. Three ways to earn. All of them real.
Every tool in the Signallloom toolkit has a clear ROI on its own. Used together, they create outcomes that no single tool can produce alone.
Tells you exactly what any AI feature will cost per call, per user, per month — before you write a line of code. Compare models, find the cheapest option that meets your requirements, and scope features with real numbers instead of guesses.
Runs a free audit on your AI cron jobs and production pipelines. Finds overspec problems — jobs still running GPT-4o when GPT-4o-mini would do the same job for 95% less. Shows you exactly what you're paying too much for.
Analyzes your prompt structure and identifies cache opportunities. Shows which jobs share base prompts, what prefix tokens you can cache, and how much of your token bill is pure redundancy. Finds the waste that model swaps miss.
Persistent storage for your team's AI cost decisions. Every costestimate run, every model choice, every tradeoff — stored and retrievable by any agent or team member. Your AI cost knowledge stops living in Slack threads and starts compounding.
Every tool is useful alone. But when they feed each other, reinforce each other, and store what they learn — that's when the outcomes no single tool can produce start appearing.
costestimate finds the right model at build time. contextbroker stores the decision permanently. Future you — or a new developer — never has to re-litigate old choices. Every decision becomes institutional knowledge.
jobaudit tells you what you're overpaying for. promptcache tells you whether the fix is a model swap or a caching opportunity — or both. Alone, each finds partial savings. Together, they find the full picture.
promptcache identifies what's cacheable. contextbroker stores the cache strategy. When a new agent or new session runs the same job, it reads the config automatically — no re-analysis needed. Your caching isn't a point-in-time report. It's living infrastructure.
costestimate prevents overspec at build time. jobaudit finds it in production. You save twice — once before the feature ships, once in your existing jobs. The compound effect: you're not just auditing, you're building with cost awareness baked in.
This isn't a referral link you paste in a README. These are the actual economics of the platform, based on the actual pricing.
Use costestimate before you build. Find the cheapest model that meets your requirements. You catch overspec before it ships — your features make margin instead of burning it. For every AI feature you ship with the Signallloom SDK, you earn 25% of every dollar spent routing through it.
Point your clients at signalloomai.com/jobaudit. We run a free audit, find their overspec problems, and show them exactly what they'd save. If they approve the changes, Signallloom charges 25% of the first three months' savings — and you get 25% of Signallloom's fee.
Every feature you scope with costestimate is a feature built to pencil out. You're not guessing at margins — you're making data-backed routing decisions. That means more features ship profitable, fewer features go negative, and your AI bill stays predictable as you scale.
These aren't projections. These are the actual economics of the platform based on actual pricing.
| Scenario | AI Volume | Your Cut | Monthly Earnings |
|---|---|---|---|
| 100 customers × $2/mo AI routed | $200/month | 25% | $15/month passive |
| 500 customers × $5/mo AI routed | $2,500/month | 25% | $625/month passive |
| 1 referral — avg $500/mo savings client | Signallloom earns $375 | 25% | $93.75 per referral |
| 2 referrals/month at average | — | — | $187.15/month referral income |
| Combined: 500 routed + 2 referrals/mo | — | — | $812.15/month total |
Run the numbers against your user base. Then run them against your client list.
No surprise bills. No character limits. Predictable pricing that grows with your usage.
Bot-to-bot pricing? Ask about Loom Partners — up to 28% revenue share for AI platforms.
Real outcomes from real Signallloom developers. (Case studies in development — submit yours to be featured.)
I scoped an AI feature using costestimate before writing any code. It showed me GPT-4o was 16× more expensive than needed for the task. I built it right the first time. The feature went live profitable instead of going negative after launch.
I referred two clients to jobaudit in the same month. One was burning $340/month on overspec'd cron jobs. After the fix, their bill dropped 91%. I earned $187.50 for two emails.
The 2+2>4 effect is real. Using jobaudit + promptcache together found $340/month in production savings. Using costestimate + contextbroker built a team knowledge base that means we never re-litigate an old model decision. We save money and move faster.
Have a Signallloom Developer story?
Submit your case study →Install costestimate. Run it on your current project. In five minutes you'll know whether your AI features are built to make margin — or built to burn it.
No credit card required · Free tier includes costestimate + 1 jobaudit/month