Exceeds

MARCH 2026

bvrithyderabad.edu.in Engineering AI Productivity Report

A focused summary of AI adoption, productivity lift, and code quality for the bvrithyderabad.edu.in engineering team.

See how AI-active teams rank this week on the Exceeds Leaderboards.

The bvrithyderabad.edu.in engineering team reports 50.0% AI adoption, 1.10× productivity lift, and 23.9% code quality across recent work.

These metrics track how AI integrates into delivery pipelines, how throughput changes when assistance is used, and the health of AI-supported code review outcomes.

What this report measures

We analyze commits and diffs to estimate AI adoption, productivity lift, and code quality for your engineering organization.

How to interpret these metrics

Use these signals to understand how AI assistance fits into day-to-day development, where enablement efforts drive throughput, and how review practices keep quality steady.

AI Adoption Rate

MODERATE

50.0%

AI assistance is present in 50.0% of recent commits for bvrithyderabad.edu.in.

AI Productivity Lift

MODERATE

1.10×

AI-enabled workflows deliver an estimated 10% lift in throughput.

AI Code Quality

LOW

23.9%

Review insights show 23.9% overall code health on AI-supported changes.

How is the bvrithyderabad.edu.in team performing with AI?

The bvrithyderabad.edu.in engineering team reports 50.0% AI adoption, translating into 1.10× productivity lift while sustaining 23.9% code quality. These outcomes suggest AI-supported reviews are embedded in day-to-day delivery without trading off reliability.

Manager Questions Answered

Real questions engineering leaders ask about AI productivity, with live benchmarks and company-specific data.

What's a good company AI adoption rate?

bvrithyderabad.edu.in is at 50.0%. This is 6.2pp above the community median (43.7%)..

50.0%

Roughly in line43.7% Community Median

Spot squads sitting below the median and pair them with high-adoption champions to share workflows.

Does AI actually make developers faster?

bvrithyderabad.edu.in operates at 1.10×. This is 0.03× below the community median (1.13×)..

1.10×

Roughly in line1.13× Community Median

Instrument reviewer assignment and AI summaries to trim the slowest merge steps and edge past the median.

How does AI affect code quality?

bvrithyderabad.edu.in holds AI-assisted quality at 23.9%. This is 0.6pp above the community median (23.3%)..

23.9%

Roughly in line23.3% Community Median

Invest in AI-specific test checklists and shadow reviews to keep quality slightly ahead of peers.

How evenly is AI use distributed across our team?

AI usage is broad—top contributors represent 36.7% of AI commits.

36.7%

Keep rotating enablement leads and pair senior reviewers with new AI adopters to retain distribution.

How can I prove AI ROI to executives?

bvrithyderabad.edu.in has a solid ROI signal with room to strengthen either adoption, lift, or quality before presenting to executives.

Document case studies where AI accelerates delivery while maintaining quality, and expand playbooks across teams.

See how your full organization compares

Unlock personalized insights across all your repositories, teams, and contributors.

Securely connect Exceeds with your codebase to get commit-level insights on AI adoption and performance.

How Your Company Ranks

See how top engineering organizations compare across AI adoption, productivity lift, and code quality.

AI Adoption

% of commits with AI assistance

Companies in this quartile:

DI

dimagi.com

(87.5%)

PO

postgresql.org

(87.5%)

BL

bloq.com

(21.4%)

DA

daimond113.com

(21.4%)

Top 25% of teams adopt AI in 65-75% of their commits.

Productivity Lift

Cycle-time improvement vs baseline

Companies in this quartile:

AC

acad.pucrs.br

(1.12×)

MC

mcornholio.ru

(1.12×)

QU

querifylabs.com

(1.01×)

HR

hrvy.uk

(1.01×)

Top performers sustain 1.5× cycle-time improvements over six months when embedding AI into workflows.

Code Quality

Post-merge defect rate

Companies in this quartile:

IN

inngest.com

(701.7%)

ID

idesie.com

(649.2%)

GZ

gzgz.dev

(20.0%)

GW

gwu.edu

(20.0%)

Top 25% maintain quality above 92% while expanding AI usage, pairing automation with rigorous guardrails.

Rankings based on aggregated Exceeds AI dataset of 1.2M commits across open-source and enterprise engineering teams (Q4 2025).

Top contributors

Top contributors combine high AI adoption and quality output. Encourage internal sharing of best practices.

DL

DUPPANAPUDI LOHITHA

Commits131
AI Usage92.0%
Productivity Lift1.12x
Code Quality20.0%
LS

Lingala Sai Krushini

Commits23
AI Usage45.1%
Productivity Lift1.12x
Code Quality20.0%
AK

AKSHAYA-SUNNAM

Commits23
AI Usage40.0%
Productivity Lift1.12x
Code Quality20.0%
CH

Chigurla_Sreeja

Commits27
AI Usage47.7%
Productivity Lift1.12x
Code Quality20.0%
36

3688tjvjf

Commits19
AI Usage46.0%
Productivity Lift1.12x
Code Quality20.0%

Encourage knowledge transfer from top AI users to others through internal mentoring or recorded "AI coding walkthroughs." Balanced adoption across the team typically improves overall performance by 12-15%.

Cross-Organization Network

Shared Repositories

5

24wh1a05j3-art

NareshCSE/Java24CSEC

allaangel

No repositories listed

divvyakrupa19

NareshCSE/Java24CSEC

24WH1A05B3

No repositories listed

Akshithapoojari

No repositories listed

Anjali-521

NareshCSE/Java24CSEC

Activity

442 Commits

Your Network

90 People
ananya792
Member
sravani-12-1
Member
varshak200529
Member
lohitha436
Member
gayathri817
Member
AKSHAYA-SUNNAM
Member
Mona-chandrika
Member
LingalaSaikrushini
Member
24wh1a0565
Member

Why these metrics matter for engineering managers

Faster delivery

1.4x lift → predictable roadmaps

Safer velocity

93% quality → lower rollback risk

Equitable gains

AI less dependency on heroes

Governance

Depth monitoring audit-ready

ExceedsExceeds AI

Turns these insights into daily coaching and automatic alerts, helping managers balance speed with sustainability.

See the truth of AI impact

Adoption + lift + quality in one view

Learn more

Know where to act first

Repo and role level "lift potential"

Learn more

Prove ROI

Export executive snapshots and benchmarks

Learn more