Dapta — 10× PR Velocity with Optibot | Optimal

How Dapta, a Voice AI Company, 10×'d Their PR Velocity Using Optibot

When almost everyone on Dapta's team started pushing code, PR volume jumped 8–10×. Dapta replaced slow manual reviews and an unreliable AI tool with Optibot — getting deep, full-context reviews in 1–2 minutes on every PR while Optimal AI Insights tracked their velocity in real time.

PR Velocity Increase

8–10×
As AI let engineers and non-engineers alike ship code, Dapta's PR volume jumped 8–10× — and Optibot reviewed all of it.

Time to Full Review

1–2 min
Every PR gets a deep, full-context review in one to two minutes, replacing slow manual reviews and an old, unreliable AI tool.

PRs Reviewed in 90 Days

2,700+
Across 16 active seats — roughly 170 PRs per engineer — every line is checked, verified, and scanned for security issues and tech debt.

"Having Optibot has been like having a dedicated engineer that is just doing code reviews. Every line of code we ship, Optibot checks it, verifies it, and finds security issues. It became a critical part of our workflow almost immediately."

Felipe Gomez
Chief Product & Technology Officer, Dapta

Dapta is moving fast. Its platform deploys voice agents that let SMBs put AI to work across sales and operations. The way Dapta builds has fundamentally changed. The development cycle has compressed so much that there's no longer a separate designer, project manager, or product manager handing work down the line. Engineers, product owners, product specialists, and even product leadership prototyping in Node and Python all ship code directly. That pushed Dapta's PR volume up 8–10×.

That velocity created a review problem. With so many contributions a day, code and design started to drift — "everything looks different," as the team put it. Manual reviews couldn't keep up, and a code-review AI tool Dapta had been using fell short on quality. After adopting Optibot, every line of code shipped is now checked, verified, and scanned for security issues and tech debt in one to two minutes per PR.

Paired with Optimal AI Insights, Dapta now sees how its engineering velocity is changing in real time, streamed directly from GitHub.

The Problem

Everyone (and Their Agents) Started Shipping Code, and Reviews Couldn't Keep Up

As AI unlocked shipping for the entire org, PR volume exploded and the review layer fell behind:

"What started out as just the engineers using Optibot for code review has now moved into product owners, product specialists, and pretty much anyone that ships code at Dapta."

Felipe Gomez
Chief Product & Technology Officer, Dapta

Without a fast, trustworthy review layer, Dapta couldn't safely convert its new shipping velocity into shipped product.

The Solution

Reviews in Under 2 Minutes, and Velocity Tracked Across 16 Engineers

Dapta integrated Optibot as the automated reviewer on every PR, starting with its most active, most complex repo and extending across the codebase. Alongside it, Insights turned GitHub activity into a live view of engineering productivity.

"We started out just using Optibot inside GitHub, but then eventually we used all of the plugins as well as the skills available within Optibot in the marketplaces. Now every line of code shipped, Optibot checks it, verifies it, finds security issues, and consistently finds tech debt."

Felipe Gomez
Chief Product & Technology Officer, Dapta

The Results

8–10× More PRs Shipped, Every One Reviewed in Minutes, Quality Intact

Optibot became a permanent part of how Dapta builds, and it spread far beyond the engineering team:

"I'm seeing the Insights data every day now. It's been very useful in our one-on-ones — to compare and let people see their own performance."

Felipe Gomez
Chief Product & Technology Officer, Dapta

The Impact in Numbers

Before and after metrics for Dapta's team using Optimal AI

Real numbers verified by the leaders using the tech.

Metric Before Optibot After Optibot Improvement
PR Velocity Manual reviews couldn't keep up as everyone began shipping Every PR reviewed regardless of volume 8–10× PR throughput
Review Turnaround Slow manual reviews; prior AI tool lagged Deep, full-context review on every PR 1–2 minutes per PR
Review Coverage Inconsistent; quality gaps with prior tool Every line checked, verified & security-scanned 2,700+ PRs in 90 days
Code & Design Consistency Drift across a fast-moving, multi-contributor codebase Standards enforced automatically on every PR Consistent across repos
Adoption Engineers only Engineers + product owners + specialists Org-wide (16 of 17 seats)
Productivity Visibility No real-time view of velocity Insights streams GitHub data — velocity per engineer & agentic productivity Real-time, used daily

By the numbers — last 90 days (Mar 17 → Jun 17, 2026): 2,704 reviews · 2,634 PR summaries · 143 comment replies · 16 of 17 seats active (94.1% utilization). All activity from the Dapta-Tech organization.