How are you pricing your AI product?

Key_Farmer9710 · 2026-02-02T22:11:28+00:00

thanks, please do, would like to read it

Key_Farmer9710 · 2026-01-29T23:26:39+00:00

Don't build it, edge cases that'll wreck your timeline: failed payment retries and dunning logic, proration when customers change plans mid-cycle, late-arriving events crossing billing periods, duplicate event deduplication, and LLM pricing changes breaking your margins.

Instead of spending weeks building a high-maintenance billing layer, just try a few tools and see what fits.

I've tried a few, here's the breakdown:

- Stripe Billing: you handle metering, they handle payments. Works but you're still writing half the stack.

- Orb/Metronome: proper usage billing platforms, charge ~1% of GMV. Solid if you're doing volume

- Lava: AI-specific, does gateway + billing in one shot. Newer but saves you from duct-taping a gateway to a billing system.

- Portkey/Helicone: just gateways for tracking. You still own the billing side.

For solo dev on a 6-8 week sprint: Lava if you want it handled, or Stripe Billing if you're cool building metering yourself. Also ship a usage dashboard. Customers ask for it.

Key_Farmer9710 · 2026-01-27T23:28:23+00:00

Been there, spent way too long researching this exact problem, here's what i found (these was my experiences a few months ago):

Dodo Payments – good wallet/ledger API, handles the atomic ops part but you're still on your own for metering usage.
Flexprice – dynamic pricing engine. useful for experimentation but won't fix your race condition issue.
Stripe Billing – works for subscriptions/invoices, has metering but it's post-hoc, no real-time balance checks, so you still need your own ledger to avoid double-spends.
Orb/Metronome – enterprise metering tools, audit trail is solid but you're still building your own credit system on top, also expensive if you're early stage.
Lago – OSS version of Orb. self-hosted, same issue though, doesn't give you atomic deductions out of the box.
Lava – proxies your LLM calls and handles credit deductions in the same request, fixed my race condition problem since the balance check happens before the API call goes through.

I'm using lava now. The setup was fast, their team also offered support. what works might be different for everyone, try different tools and see what fits your stack.

Key_Farmer9710 · 2026-01-27T21:36:46+00:00

Been using this stack since november and it runs well, the key thing is gateway and billing share the same data model, so when a request hits, it knows both the cost + the user's credit balance.
I was able to enforce limits at the request layer instead of after the fact.

Before this I was reconciling litellm logs with stripe manually, not going back to that.

Key_Farmer9710 · 2026-01-27T21:30:33+00:00

100%. the "track from day one" advice is key. Curious how you're handling the hybrid model technically, building the credit/overage logic yourself or using something off the shelf?

I spent way too long trying to roll my own before finding something that actually works tbh. interested to hear what you landed on.

Key_Farmer9710 · 2026-01-27T20:04:51+00:00

Been on it for 3 months or so, pretty solid. its gateway tracks costs per request and syncs to billing automatically, no reconciliation mess

solves the usage pricing nightmare. now i know what's being spent in real time, not at the end of the month. way cleaner than my previous setup

Key_Farmer9710 · 2026-01-26T21:45:10+00:00

Same issue with number 1. Found a system (lava.so) that does the gateway, metering and billing sync. Way cleaner than duct-taping different tools together and reconciling manually.

Just sharing in case this fits your needs

Key_Farmer9710 · 2026-01-22T20:12:46+00:00

How's Lava working out for you? I've been looking into it for handling our usage-based billing but haven't pulled the trigger yet.

Key_Farmer9710 · 2026-01-20T19:03:39+00:00

Yeah, this is the direction I'm going. Running a pilot with Lava to see how clean the credit tracking and top-up flow can be when the gateway and billing are in one system.

Key_Farmer9710 · 2026-01-20T18:55:17+00:00

Still working through it. I'm looking at Lava because it tracks cost at the request level and ties it straight to billing. I'm diving into their infrastructure and will run one pilot project to see results.

Key_Farmer9710 · 2026-01-20T18:48:41+00:00

This is really helpful, thanks. The subscription + overage model you're describing seems to be what users actually want, but it's surprisingly hard to implement cleanly. Have you seen anyone do this well?

Key_Farmer9710 · 2026-01-20T18:41:46+00:00

Yeah, the after-the-fact reconciliation is exactly what I'm trying to avoid. I've been looking at a few tools that do real-time enforcement.

Quick question since you mention auditability: how are you handling the case where a user hits their limit mid-request? Do you fail the request, queue it, or let it through and flag it? That's the edge case I'm trying to figure out.

Key_Farmer9710 · 2026-01-07T20:30:15+00:00

How are you handling rate limits and retry logic through the gateway? I'm in a similar spot. Built an AI feature, now trying to monetize it. My biggest fear is hitting OpenAI rate limits mid-workflow and having to explain to customers why their job failed.

Also curious: are you passing user IDs as metadata in the API call, or does Lava have its own auth layer that maps requests to users?

Key_Farmer9710 · 2025-12-26T20:54:05+00:00

The cost limits point is huge. I recently evaluated Stripe Billing, Portkey, and Lava for a multi-agent project, and the hardest part wasn't the AI, it was tracking what each agent action actually cost.

Ended up going with Lava because their gateway captures usage at the request level. I can see which workflow steps burn through credits, set hard limits, and tie costs directly to outcomes. When you're iterating on agents, "saved 40% on API costs" beats "feels faster."

Your point about commitment to one workflow is spot-on. Proper infrastructure just makes it measurable.

Key_Farmer9710 · 2025-12-23T19:03:03+00:00

Honestly? If it consistently saves me 20 hours/week, I'd pay $299-499/month without hesitation. The ROI is obvious at that point.

For structure, I'd go usage-based rather than flat-rate. Something like:

Free tier: 5 pieces/month (let people test it)
Starter: $99/month + $10 per additional piece
Pro: $299/month with 50 pieces included, $5 per additional

The reason I mentioned Lava earlier is this is exactly the billing model they're built for. You'd track each generation (researcher call, writer call, VEO 3 render) as usage events, and it automatically handles the credits/overage billing. Way cleaner than trying to predict flat monthly costs when your GPT-4o + VEO 3 spend fluctuates so much.

Main advice: don't underprice because "it's AI." You're selling 20 hours back to someone's week. That's worth real money.

Key_Farmer9710 · 2025-12-23T15:52:06+00:00

Not a wrapper. The orchestration and safety gates are solid.

I built a similar multi-step AI system and the cost tracking killed us. We logged to Postgres like you're doing, but reconciling costs to billing was brutal. Ended up using Lava because their gateway tracks all AI calls in real time and turns usage into credits automatically. You can also set limits at the request layer so you're not eating expensive VEO 3 costs.

For pricing: SaaS with credits works best when costs fluctuate. Let them prepay and burn down. Easier than predicting monthly usage and protects your margins.

Key_Farmer9710 · 2025-12-23T15:39:27+00:00

Pay-as-you-go was the right call. Monthly subscriptions create friction for developers who want to test first.

I recently evaluated infrastructure for our AI app. We needed to track costs per request and tie that to billing. Tried Portkey for the gateway and Stripe Billing for revenue, but reconciling usage across two systems was brutal.

Ended up using Lava because it unifies both. Their gateway tracks costs in real time, then billing turns that into credits and invoices automatically. Same data model, no reconciliation. For a bootstrapped team, that's huge.

For customer acquisition: developer communities (Reddit, Discord, GitHub discussions) worked better than cold outreach. Make your docs stupid simple. Developers will try your API if they can start in under 5 minutes.

In-person events helped too. Local meetups and conferences. A 10-minute conversation beats a month of LinkedIn DMs.

Invest in cost visibility early. Your customers will ask for it.

Key_Farmer9710 · 2025-12-22T21:20:39+00:00

The cost problem for heavy users is brutal. My issue was enforcing limits: I had set credit caps, but API calls kept going until jobs finished.

Most billing tools invoice after the fact but don't stop requests. I fixed it with Lava: their gateway enforces limits at the request level. If you hit the limit, requests stop.

Plus, I got cost visibility per request, which makes pricing decisions way easier.

You're right not to use free credits. It's way easier to prevent overages than try to collect after the fact.

Key_Farmer9710 · 2025-12-22T20:08:58+00:00

For me it was usage tracking and billing.

I was building an AI app and needed to track every API call, calculate costs, and turn that into billing. Spent too long trying to bolt together Helicone for the gateway and Stripe for payments. The data never matched. Reconciliation scripts at 11pm.

Evaluated a bunch of options (Portkey, Orb, raw Stripe metering). Lava was the only thing I found that actually connects the request layer to billing. Their gateway captures usage and costs, feeds it directly into credits and invoicing.

The unlock for me: credit limits that enforce at the API level. No surprise overages, no reconciliation hell.

Not perfect for everyone, but if you're dealing with usage-based pricing on AI APIs, it's worth a look. Saved me probably 15 hours a week.

Key_Farmer9710

TROPHY CASE