Tech Talent Search & Analytics

Powerful AI-based search and analytics for natural talent pools on GitHub, StackOverlow, Medium, etc. Novel approaches to discover, evaluate and engage tech stars 👨‍🚀



☁️-native shenanigans for the ENT



Helm charts from kustomized YAML files

go, smarty

2321 contributions


devscanr profiles

Lee Payne

Lee PayneHireable

Senior DevOps
Dubai, UAE
github rank
Top 10%
dev. experience
~10 years, Senior
top skills
aws, docker, kubernetes, elk, azure, redis, gcp
Machine Learning, Music, Cryptography
350K+ Dev. Profiles
Worldwide tech talent, not spoiled by extra attention yet. Aggregated contacts and accounts.
Unique Insights
AI-inferred data. Talent interests & competences. Global rankings. Connection graphs.
Intelligent Search
Convenient UI with smart filters and autocompletion. Enjoy pre-evaluated profiles and ATS integrations.
Affordable Price
Unlimited contact views & searches. No hidden fees. Budget-friendly, even for HR beginners.

Why DevScanr?

IT professionals don’t babysit their resumes 👶. They are busy coding on GitHub, helping colleagues on StackOverflow, sharing knowledge on Medium... Unfortunately, dev. platforms were never designed or intended for sourcing. Even with rare search functionality you typically see just a tiny fraction:
devops location:California type:users (< 200 users out of 4000)...

Grover Olson

Grover Olson

Frontend Developer
Liliya Mckee

Liliya Mckee

Backend Developer
 Saoirse Dotson

Saoirse Dotson

Data Scientist

find more with

Automated Sourcing

The majority of Californian devops on GitHub are unsearchable – for one reason or another. Empty or shortened locations, missing specializations, ☁️ icons instead of proper words, skill aliases you didn’t expect... Let’s see how DevScanr workarounds that.

Search Automation
A naive search can be improved with boolean queries and precollected lists of synonyms. But you’ll need an automation to get further. Our engineers have developed data pipelines, AI & search engines – all to take your sourcing efficiency to the next level.
Data Enrichment
The platform fixes unsearchable / invisible profiles with a dedicated enrichment step. Normalized data allows to switch from a primitive keyword-based search to a smarter, knowledge-based (more below) and get more results per search.
Our goal is to make millions of active profiles on GitHub, StackOverflow, etc. searchable and engageable. So talent who dislike LinkedIn (or have it blocked in their countries) still have an opportunity to find their dream jobs. AND ("Serbia" OR "Republika Srbija") AND ("Frontend Developer" OR "FE" OR "Frontend Engineer") AND ("react" AND "typescript" AND "tailwind")

appreciate the

Intelligent Filters

DevScanr provides geolocation-aware and term-aware search. It understands what you mean. Search results are widened or narrowed, as you would expect. Autocomplete just workstm and search boxes properly support copy-paste.

Location Filter
The platform knows that “Los Ángeles”, “City Los Angeles”, “LA” are the same thing. It knows that “Poland” includes “Kraków” with all transliterations, as well as “Warsaw” with all typos. Compare that to GitHub or sites with no search, where you can only X-Ray.
Specialization Filter
The platform knows that “Data Scientist”, “Big Data Developers”, “Data Analysts” and “Machine Learning” are related specializations. That “Frontend Developer” can be written as a ”Frontend Engineer” or ”FE”. It can even find talent without explicitly mentioned titles (more below).
Skills Filter
The platform knows that JS, ES, ES6, JavaScript, EcmaScript are synonyms. It remembers relations between C, Python, Cython, and CPython so you don’t have to. Save the effort of trying to learn all the buzzwords and focus on hiring instead.


Healing websites and apps 🚑



Automation of Form Testing

mocha, javascript

1634 contributions

Kylie Foster

Kylie FosterHireable

Quality Assurance
top skills
typescript, unit-tests, mocha, selenium, bdd, pytest, cassandra, gherkin, cypress

save time with

Structured Data

DevScanr aggregates and structures scattered user accounts across the Internet. It mines and highlights the important data. No need to surf through repositories, gists, forks, stars, posts, followers, commits to extract talent’ competences and interests.

Contacts & Hireability
The platform captures important (and sometimes inaccessible) pieces of data. Contacts, statuses, titles, skills are mined, merged and deduplicated. The end result is a single convenient profile card with external links with no view limits.
Open Source Analysis
The platform analizes user accounts and repositories. It tracks programming languages, libraries, frameworks, checks how often they were used and so on. Based on the obtained statistics, the platform generates an accessible talent overview.
Text + Activity Analysis
There’s always more data to dig and it’s far from being limited to code. We plan to add Linguistic Competence and other Soft Skills metrics to the platform in the future. As well as dynamic views of talent’ interests reflecting their career goals.


☁️-native shenanigans for the ENT
Lee Payne

Lee PayneHireable

Senior DevOps
dev. experience
~10 years, Senior

learn more with

AI Inference

Engineering areas evolve and overlap, so it’s often hard to distinguish between a Backend and a Frontend developer. It’s even harder to estimate one’s competence. DevScanr is equipped with algorithms and AI to fill missing pieces and infer labels for you.

Inferred Specialization
The platform listens to what talent claim, but it also looks into projects, repositories, articles, and whatnot to accurately infer user skills, professional and personal interests, and even specializations with confidence scores.
Inferred Experience
Only 10% of GitHub users explicitly state their tenure. While the topic of experience is the most complex (each one counts differently) it’s a very important piece of information. The platform uses its own algorithm to accurately predict years of experience and competence.
Liliya Mckee

Liliya Mckee

Backend Developer
github rank
Top 10%
Computer Vision, Artificial Intelligence, Open-Source, Deep Learning

I've noticed your interest in ML.
We have an open job at Giant AI.

11:12 AM


I'm interested. Let's talk!

11:20 AM

get insights from

Interests, ranks, networks

The Talent Market is competitive. DevScanr shares even more unique, data-driven insights to help your recruitment and engagement. Talent interests, strengths and weaknesses, social connections,... so many helpful hints are there, waiting to be uncovered.

Professional Interests
Looking for a Backend Engineer for an AI startup? DevScanr can find a backend-er who casually experiments with Machine Learning or follows ML/AI gurus. Such talent will be more interested to join and more motivated to stay.
Developer Rank
DevScanr ranks each developer for a given location and specialization. This rank is evaluated by an algorithm similar to Google ranking. Looking for a tech star? Pay attention to profiles from the Top-10%. Seeking a “promising junior”? Go for the Above-Average.
Networks + Other Goodies
More to come. Stay tuned...

Sourcing Flow ✨

GitHub, StackOverflow, Medium... are not sourcing platforms. Even if you manage to find the desired amount of prospects, next challenge is to export and organize the data. DevScanr, conversely, is made with the sourcing flow in mind!


Experiment with different filter combinations and store them in a project for when you need them.


Take notes on the candidate profiles, evaluate them, and add the best matches to the project.


When you are ready to engage prospects, export the talent list and import it in a preferred ATS.

Recently Launched and Growing

DevScanr has over 300,000 profiles of developers, programmers, software and hardware engineers, QAs and security specialists, scientists, analysts, operations, designers, even 🦄. All competence levels are covered!
Web Developers
Data Scientists
Security & Devops
Mobile & Game Devs

Boost Your Recruitment Process

We are committed to finding the best talent for our customers and partners.
  Discovering tech stars    in any weather and light conditions.

in-country search

$16  / month
  • Search in one country
  • Unlimited contact views
  • Unlimited # of searches
  • 2500 profiles per search
  • 5 active projects
  • 10 filter sets per project

on-planet search

$32  / month
  • Search in any location
  • Unlimited contact views
  • Unlimited # of searches
  • 5000 profiles per search
  • 10 active projects
  • 20 filter sets per project

in-galaxy search

  • All the benefits of the previous
  • Talent pool for your needs
  • Personal customer support
  • Unlimited profiles per search
  • Unlimited active projects


Can’t find the answer you’re looking for?
Reach out to our customer support team.

Is DevScanr a recruitment agency? How do you ensure privacy?

DevScanr is exclusively a sourcing tool 🔭. The team behind the project has a decade of experience in related fields. We have worked and collaborated with staffing companies and industry experts. We’re going to blog more about our vision in the near future.

Only public data is read from GitHub, StackOverflow and other sources. The data is stored in anonymized form, excluding all privacy concerns. As for our clients... everything, obviously, stays confidential and is never exposed. For more information please check our Privacy Policy or ask us directly.

So DevScanr is a resume database?

No, it’s not. We think that resume platforms are overvalued and there’re easier and less expensive ways to close positions. Best talent are already employed (statistically speaking) so their resumes are always out of date. There’re, indeed, millions of accounts on LinkedIn but what % of them visits the site at least monthly?

We strongly believe that quality beats quantity in recruitment. That it’s appropriate to explore new ways to evaluate, reach and engage candidates. Having noted this, DevScanr aggregates talent resume links, among other contacts, so you can freely visit all associated URLs. Unlimited number of times!

Still, what’s wrong with LinkedIn? Everyone is using it.

Nothing wrong, if you’re satisfied with single-digit response rates... More and more engineers, especially on the stronger side, abandon their resumes and corresponding sites. Why? They hate manipulative feeds, hate being spammed with irrelevant proposals and advertisements. Unread DMs accumulate, answers to everyone would take forever. One day they simply stop to care 🤷‍♂️.

Which does not mean they’re forever unreachable. If you think the world ouside of LinkedIn consists of “already hired”, “cold contacts” – you seriously miss the point. The same devs are being actively hired via their friends, subscription threads, events, etc. alternative medias and means.

We believe that your (cold lead) response rates should start at 10%, not end. That hiring can be much more productive. But to achieve that, it’s necessary to learn who your candidates really are. What are their preferences, interests, social connections. The best offers are individualized. Resumes are too formal, too generic, too boring to extract the information you need.

How does DevScanr compare to other alternatives?

Recruiting platforms are mostly expensive, all-in-one solutions with rich functionality. Besides search, they include layers of automation, messaging, integrations. The downside is a steep price, typically starting from $100 per month per seat. Some platforms, like SeekOut or AmazingHiring, are even more expensive ($400+). They provide massive databases, not limited to tech talent.

The opposite side of the spectrum is represented by numerous cheap (or free) browser extensions, tools for creating boolean queries, etc. “one-trick pony” tools. They often lack support and functionality.

DevScanr aims to be a middle ground between both extremes. It’s exclusively a sourcing tool, focused on tech talent, with a number of unique features. It’s designed to integrate in your pipelines seamlessly. And we want to keep the service affordable for all recruiters.

How many credits are included in DevScanr plans?

Mainstream platforms earn money via limits on key actions. For example, LinkedIn Recruiter allows “30 messages” and “20 searches” for $180 per seat, per month. It’s expected and desired that your credits exhaust fast. DevScanr applies only a (yet informal) Fair Use policy for our clients and partners. No artificial rules to make you overpay!

What’s so good about GitHub? Why do you focus on it?

Think of GitHub as a social network for IT people. Even if it’s not positioned this way – it factually is. While some other competitive platforms, like Gitlab, handle a lot of commercial traffic, GitHub stays the go-to platform for the open source. The majority of important libraries, across many ecosystems, are maintained there. Which creates a synergetic effect.

There’re a few major benefits for sourcing on such platforms. You catch people you’d never notice or reach on LinkedIn. Talented students who managed to collect follower bases before their first resumes. Seasoned developers, who don’t open their LI pages anymore (being tired of generic & spammy job messages). Introvers, more focused on code than on social activities. People who dislike how their resumes look on LI and hosting their own resume sites. So many categories...

To be fair, some % of engineers don’t trust Microsoft and avoid both LinkedIn and GitHub. Some are obsessed with HackerRank... some ignore it. The point is: it’s important to learn which communities / groups of people prefer which platform, and to act accordingly.

Another benefit of GitHub are social proofs that can be extremely helpful. DevScanr calculates a GitHub rank (using an algorithm similar to what Google/Yandex use to evalute web pages). The rank is derived from a number of followers but it’s much more involved than a simple count. To simplify, a person followed by Linus Torwalds alone would rank much higher than someone followed by an army of bots. Unfortunately, he does not follow anyone :)

So there’s Rank and Experience filters. Now by simply setting both to HIGH RANK + LOW EXPERIENCE combination you discover engineers who are ahead of others, at least in the eyes of the community. A trivial but powerful way to find promising interns or juniors.

The same network of follower/following links can be used to find social connections and seek recommendations. Cold contacts become warm if you simply refer to the right people. Or hot, if you’re referred by them... The most powerful efficiency boosters are hidden there, for those who knows how and where to dig. Or perhaps it’s easier to keep bombarding more LI inboxes with more “amazing opportunities” instead.