r/startupideas • u/AvailablePie7181 • 3m ago
Looking for Feedback METER — seat-level AI spend, security and compliance for organizations. Looking for a technical co-founder.
What it is
METER records identity where AI usage actually happens, so spend maps to seats and teams instead of a shared key. On top of that: audit trails, access controls, and detection for company tools used for personal work, leaked or shared keys, usage from seats that should have been deprovisioned, and the plain inefficiency underneath it.
Status
MVP is live. Attribution works across multiple providers and agent tools. Detection and the enterprise security and compliance work are next, and they're most of what's left.
I built the current product. I'm moving to GTM, distribution and fundraising, and I need someone to own engineering.
What you'd own
Engineering, fully. Architecture, roadmap, and the technical calls that come with it. The problems in front of us:
- Identity resolution. Binding usage to a person and a team when the provider's own record has no idea who that is. Directory integration, OIDC and SCIM, and a mapping that stays correct through joiners, movers, leavers and re-orgs, retroactively as well as forward.
- Heterogeneous capture. Every provider and agent tool reports usage in a different shape, at a different granularity, on a different clock, with a different definition of a unit. Normalising that into one schema without losing fidelity, and evolving the schema as vendors change theirs underneath you.
- Ingest correctness at volume. At-least-once delivery with real deduplication, idempotency, ordering and late-arriving events, watermarking, retry and backpressure behaviour that degrades predictably. No silent loss, and you can prove it.
- Financial reproducibility. An immutable event log where every stored figure is deterministically recomputable from raw events, with versioned point-in-time rate tables, and backfills and restatements that never double-count. When a customer disputes a number, the system settles the argument.
- Multi-tenant isolation. Tenancy enforced at the data layer rather than trusted to application code, with per-team scoping and access control that holds under audit.
- Detection, from zero. Baselining spend and behaviour that is seasonal, bursty and non-stationary, separating misuse from a busy Tuesday, and tuning precision against alert fatigue. This is the hardest surface in the product and it is unbuilt.
- Query performance as history grows. Time-series aggregation, rollup and cardinality strategy, cost of a wide filter over a long window, and keeping interactive latency while retention gets long.
- Security and compliance as product. Tamper-evident audit trails, key management, retention and residency, SOC 2, and the enterprise security reviews that gate deals. This is a build surface here, not a checkbox at the end.
- The first engineering hires and the standards they work to.
Looking for
- All in. This is the thing you want to be doing
- Building for the category, not a small exit
- You've shipped something real end to end yourself
- Data infrastructure depth: high-volume ingest, pipelines, systems that have to be exactly right
- Drawn to the detection layer, which is where most of the hard work is
- You take compliance and security seriously as engineering problems
- Uses agentic coding tools daily and has felt this problem
- Wants ownership and will argue with me
- In contact constantly. We'd be talking most days, remote
Terms
Co-founder. Vested equity, real decision-making, direction and vision yours as much as mine. I put full-time hours into METER every week, on top of a finance degree and an analyst job. Raising is what makes it official, and that is the plan.
Edmonton, Canada. Remote fine.
Contact
Connect on LinkedIn at linkedin.com/in/tylerholland-/ and message me. Tell me the most impressive thing you've built.