Why We're Building an analytics platform
So my friends and I run multiple products, and every single one of them needed to know what users actually doing, where are they dropping off, why isn't stuff converting. So, like everyone else, we did the normal thing. Get analytic tools. Then another one, because maybe the first didn't cover mobile. Then another, because we needed session replay and that meant a third dashboard, a third script tag, a third bill.
Multiply that across every product we were running, and we ended up with this sprawling, disconnected mess, one tool per product, sometimes two or three per product, none of them talking to each other. Every time we wanted a real answer about user behavior, it meant logging into four different dashboards, squinting at four different definitions of "session," and trying to mentally stitch together a story that no single tool was actually telling us.
At some point, we just have to agree that they need to be just one platform that consolidates all of this*
And yeah, that basically is the whole idea. That's where TraceIQ came from.
We never set out to build "another analytics tool." We set out to fix our own very specific, very annoying problem, and it turns out almost every developer and product team we've talked to since has the exact same problem. Too many tools, too many scripts on the page, too many half-answers, and no single source of truth for how users actually move through a product.
So we started building the one tool we actually wanted to use ourselves.
TraceIQ
TraceIQ is a developer-first behavior intelligence platform for web and mobile applications. Instead of vanity metrics, it's built to answer the questions that actually keep product and engineering teams up at night:
- What did this specific user do before things went wrong?
- Where exactly in the funnel are people dropping off, and why?
- Which journeys correlate with retention, and which quietly kill it?
- How are our critical flows, signup, checkout, onboarding, actually performing right now?
If you're a fintech team walking users through KYC, an edtech team trying to nail activation, or a SaaS company trying to figure out why trials aren't converting, you don't need another chart. You need precise, trustworthy behavioral signal you can actually act on.
That's the gap we're building TraceIQ to close.
What's inside
We designed TraceIQ as a foundation first, the core primitives every product team needs, with a clear line of sight to the smarter, AI-assisted layer on top. Here's what we're building:
1. Event tracking A durable behavioral source of truth. The SDK is micro-optimized to stay under 25 KB, runs fully asynchronously, and is designed from the ground up to leave your LCP, INP, and CLS untouched. Performance was never going to be a trade-off we accepted.
2. Funnel analytics Build custom, multi-step funnels to see exactly where users fall off, and compare success rates across variants, so you're making decisions on evidence, not intuition.
3. User timelines Drill into a single user's session and see the precise sequence of actions that preceded a checkout failure or an API timeout. This is the debugging session we wished we'd had, built into the product.
4. Session replay A ready-made layer abstraction for visual session replay pipelines, so you can watch the friction happen instead of trying to reconstruct it from logs.
5. Error diagnostics Front-end exceptions get captured the moment they happen, with stack traces automatically tied to the behavioral trail that led there. Errors stop being isolated incidents and start being part of the story.
6. AI-powered insights (on the roadmap) Automatic anomaly scoring, UX friction reports, and design suggestions, the layer that turns raw behavioral data into decisions your team can act on without digging.
We’re also designing TraceIQ to work with AI agents and developer tools. An MCP server will let copilots and internal assistants query behavioral context, event definitions, and product signals directly, so the platform can fit into workflows instead of living only behind a dashboard.
Privacy isn't an afterthought
We didn't want to bolt privacy compliance on at the end, so we built it into the foundation instead. TraceIQ is designed to track sessions using privacy-first, cookieless telemetry hashes, no PII stored on the device, no standard cookie banners required, and GDPR/CCPA compliance by default rather than by extra configuration.
Your infrastructure, your call
TraceIQ is being architected around Docker and PostgreSQL from day one, which means you'll have a real choice once we launch: spin up on our managed cloud for the fastest path to value, or self-host on your own infrastructure, AWS, Vercel, Fly.io, wherever you already live, for full data sovereignty. We don't think you should have to choose between speed and control.
We're not live yet, and that's the point
Here's the honest part of the story: TraceIQ hasn't launched. We're deep in building, testing, and refining, and we'd rather ship something genuinely solid than rush a half-finished product out the door just to hit a date.
What we do have is a waitlist, and a simple ask. If the problem we described above sounds familiar, come tell us about it.
Join the waitlist at traceiq.run
Signing up gets you:
- Early access when we open the doors
- A direct line to the team shaping the product, your workflows and pain points will genuinely influence what we build next
- First look at SDKs for web (JS), Swift, Rust, Python, Kotlin, and React Native, so your entire stack can eventually feed into one behavioral pipeline
Here's a preview of what integrating will look like once we're live, a few lines to start tracking real events:
import { traceiq } from '@traceiq/sdk-js';
traceiq.track('purchase_completed', {
amount: 89.00,
currency: 'USD',
gateway: 'stripe'
});
No heavy setup, no vendor lock-in ceremony. Just a small script and a stream of signal you can actually trust.
What's next for us
Event ingestion, funnels, timelines, replay, and error tracking are the foundation we're laying first. From there, we're headed toward AI-driven insights, cohort analysis, and deeper conversion intelligence, the parts of the product that turn "here's your data" into "here's what to do about it."
If you're a growth-stage team that needs real product analytics before you're ready to build an entire internal data platform, this is being built for you.
We're not done. We're just getting started, and we'd love to build the rest of this with you watching, and with your feedback in the room.
Let's build.