Continuous UX iteration,without the engineering queue.
Omnomesh is a UX experimentation pipeline for product teams too large to guess. It finds the change worth testing, proves it is worth testing, and ships it, as a Pull Request, governed, flagged, ready to run as a real experiment.
Three movements, one loop.
We read what you already produce.
Telemetry, commit history, support tickets, performance analytics. Omnomesh treats these as the real backlog, and ranks opportunities by signal strength before anyone writes a ticket.
Each opportunity becomes a testable claim.
A multi-agent system maps the opportunity to specific files, components and surfaces. You get a hypothesis: what we change, what we expect, how we will know.
One PR per hypothesis. Governed, reversible.
Every PR is scoped small, feature-flagged, instrumented with telemetry, and remediated against your CI until it passes. Merge or revert. The loop logs either way.
A different tool, for a different job.
Analytics tools tell you what happened. Coding agents help one engineer write faster. Neither closes the UX experimentation loop. Omnomesh is built for that specific gap.
Charts from traffic.
Code from spec.
Find. Review. Ship the UX experiment.
Funnel, cohort, and event dashboards
1Finds the UX change worth testingreads telemetry like a PM reads dashboards
Boilerplate and scaffolding on demand
2Grounds every hypothesis in real artifactsfunnel reads, repo maps, owner routing
Greenfield work from a spec or prompt
3Ships a PR, flagged, instrumented, scopedgoverned merges, reversible by design
Speeds up general development workflows
4Repeatable across surfaces, sprints, teamsthe loop compounds
How omnomesh works.
The quality you see at the end is the result of choices made at every step.
Discovery, mapping, writing, and review are separate specialist agents with their own context. You get cleaner handoffs and fewer dead-ends than a single prompt could ever produce.
Each stage emits heavy, inspectable artifacts: funnel reads, repo maps, UX rationales, test plans. The next agent works from documents, not memories, so the output stays anchored.
A red-team agent attacks every hypothesis and PR: weak priors, bad scope, unclear metric, UX harm. Anything that survives is worth a human minute.
Omnomesh adds synthetic user-intent signal from your business context and ICP expectations. It complements strong telemetry and still grounds calls when session data is thin.
Optional. Outcomes feed back into the model of your users and your product: priors update, bad assumptions retire, and the pipeline learns your surface the way a long-tenured PM would.
A note from the founder.
I'm currently in my second year of the Bachelor of Advanced Finance and Economics at the University of Queensland in Brisbane. Since early 2023, I've been using AI to teach myself how to build software and, over time, to build products of my own.
Through 2025, I was deep in a consumer product where AI agents were core to the experience. What stayed with me was not just what AI made possible, but how quickly product complexity changed the job of improving it.
The more surfaces a product has, the easier it becomes to leave valuable improvements untouched, and the harder it becomes to see the product with fresh eyes.
That is the gap Omnomesh is built around. As I iterated, I kept feeling two pressures at once: there was never enough time to improve everything that mattered, and the closer I got to the product, the harder it became to step into users' shoes and see the experience as they do.
The last six months have been about building around that problem. It feels especially relevant now, because as AI makes software easier to build, the advantage shifts toward better product judgment, stronger UX, and faster iteration on what users actually feel. You would be one of the first design partners, and the pilot is scoped so the product does the convincing, not the pitch.
Taking on a few Design Partners.
The teams that get the most out of this tend to look like this.
Limited pilot cohort
Abhiram reads every application personally and replies within 24 hours. Applying starts the conversation.