Pavo Platform
The platform forcontinual improvement.
The applied science factory to continually improveproduction systems and agents.
Purpose-built for moving production metrics: It learns how your system works, finds opportunities, builds the evaluation, and launches experiments.
demo.pavoai.com
The Vision
The future belongs to production systems that learn from experience, improve continuously, and remain steerable.
The platform
Purpose-built for engineers and leaders owning metric outcomes. Pavo sets a new standard for finding opportunities and shipping changes.
Build deep system understanding
Pavo self-onboards across your code, data, and experiments, then distils a benchmarked model of how your production system actually works.
Run parallel explorations
Designed to run multiple approaches, reducing median time to validated improvement from months to days. From finding gaps, to pushing PRs.
Move more metrics per quarter
Pavo runs opinionated projects end to end and ships the ones that hold up offline, so more validated improvements land every quarter.
Applied science factory
From a plan to a swarm of agents across gap discovery, offline evaluation, feature development and A/B tests, with checkpointed autonomy.
Learn moreStart with a metric goal. Pavo drafts a plan from your code, data, and past experiments, for your sign-off.
Spins up Agent Studio. Long-running agents explore multiple approaches in parallel, one per hypothesis.
Build ML models in parallel. Pavo writes the code, data pipelines, and features, then scores every candidate.
Ships a production build. Pavo executes the work and raises the pull request for you to approve.
Knowledge Systems
Pavo self-onboards where production knowledge lives, distils a benchmarked understanding of the product, and compounds it with every finding.
Learn moreapp.pavoai.com/knowledge
Case studies
All case studies
How Seekho replaced broadcast blasts with category-level personalization
Pavo mapped the notification system, fixed the signal driving it, and ran a phased program from four interest groups to sixteen category segments.
Read the story+43%
Notification click-through rate
+94%
Second-video initiation
How Dashverse lifted Shortfree Autoplay activation with an offline-eval loop
Pavo built an offline-eval engine to screen ~50 candidate policies without live traffic, then shipped the one variant that moved activation in production.
Read the story+3.1pp
Autoplay activation, live in production
~50
Policies screened offline before one reached users
Work with us
Bring continual improvement into production.
Pavo Enterprise
The loop, embedded.Run with you by our applied scientists.
The library
Notes from production.
Research, teardowns, and field notes on making production systems measurably better.
Talk
Compounding systems intelligenceWhy +1% on a production system is worth millions, and what it takes for an agent to own the improvement loop.Watch the talk
Compounding systems intelligenceWhy +1% on a production system is worth millions, and what it takes for an agent to own the improvement loop.Watch the talkResearch
NovaMart: we simulated a company to benchmark tribal-knowledge extractionA company executed rather than authored, so its sources causally agree, released with 51 audited tribal-knowledge claims.Read more
NovaMart: we simulated a company to benchmark tribal-knowledge extractionA company executed rather than authored, so its sources causally agree, released with 51 audited tribal-knowledge claims.Read moreResearch
The model is still not the moat: what NovaMart reveals about tribal-knowledge extractionSame model, same company: Pavo recovers 74.5% of the benchmark's tribal-knowledge claims against 62.7% for the best generalist, and six in ten claims in every run.Read more
The model is still not the moat: what NovaMart reveals about tribal-knowledge extractionSame model, same company: Pavo recovers 74.5% of the benchmark's tribal-knowledge claims against 62.7% for the best generalist, and six in ten claims in every run.Read moreResearch
System Ground Truth: What Agents Must Know About Production SystemsAgents can be right about every file and still be wrong about the system. We define the ground truth production agents need.Read more
System Ground Truth: What Agents Must Know About Production SystemsAgents can be right about every file and still be wrong about the system. We define the ground truth production agents need.Read moreSystems
Building an Enterprise Sandbox for AI AgentsWe tried to buy the sandbox. We ended up building one. This is the story of why, what we built, and what broke.Read more
Building an Enterprise Sandbox for AI AgentsWe tried to buy the sandbox. We ended up building one. This is the story of why, what we built, and what broke.Read moreSystems
Crash-Proof Custom AgentsShipping long-running agents with retries, stops, and durable state.Read more
Crash-Proof Custom AgentsShipping long-running agents with retries, stops, and durable state.Read more