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Atomic HR

Spend more time on the people behind every decision.

Turn one business problem into a focused use case and validate it around your systems, data and processes.

Start your journeyExplore use cases
Talent Acquisition

Candidate Screening

RoleAccount Executive, DACH
CandidateSarah M.
Match score87 / 100
Strong match for a first interview.

Give your team a better starting point.

HR Knowledge Hub

Centralize HR knowledge and policies.

Leave assistant

Request absences.

Employee Self-Service

Give employees instant access to HR information.

Employee Lifecycle Automation

Automate onboarding and employee processes.

See the work before you commit.

Compact product views show what the team can test. The full context opens from the use-case explorer above.

Input
PDFSarah_M_CV.pdf
Compared against Job description — Account Executive, DACH
SkillsWork experienceLanguagesLocation+ recruiter criteria
Scoreboard
Candidate
Sarah M.
Match score
87%

Six years in B2B SaaS with ownership of enterprise accounts in DACH. Directly relevant market and language fit; management exposure is informal rather than formal.

Key strengths
  • 6 years B2B SaaS experience
  • Required language skills (EN/DE)
  • Relevant market experience
Potential gaps
  • Limited people-management experience
Recommendation
Strong match for a first interview.
Edit analysisMove forward

The first pass is automated. The judgement stays with the recruiter.

Talent Acquisition

Candidate Screening

Compare candidates against one role and prepare a structured first pass for recruiter review.

Input
Job title
Senior Data Engineer
Department
Data & Analytics
Seniority
Senior
Employment type
Full-time
Location
Zurich / hybrid
Required skills
Python, dbt, Snowflake, Airflow
Your private knowledge base
Existing job descriptions
Company Benefits Guide.pdf
Employer Brand Handbook.pdf
Competency framework
Writing guidelines
Maintained by your HR admins. Never shared with other organisations, never used to train public models.
Generated job description
Export .docx
About the Role

Own the pipelines that move finance and product data into the warehouse, and the models the business reports on.

Responsibilities

Design and maintain ingestion pipelines. Review data models with analysts. Keep documentation current.

Required Skills

Python, SQL, dbt, orchestration with Airflow, warehouse modelling on Snowflake.

Nice-to-have Skills

Streaming ingestion, dimensional modelling at scale, German.

Benefits

Hybrid working, learning budget, pension contribution above statutory minimum.

Source: Company Benefits Guide.pdf
Company Culture

Small teams with real ownership, written decisions and clear responsibilities.

About the Company

A European data and technology group building products for regulated industries.

Hover a section to see where the content came from.

Talent Acquisition

Job Description Assistant

Use company knowledge, policies and competencies to prepare a role for review.

Validate before you commit.

01

Define the use case

Choose one problem with a clear business reason to solve it.

  • Understand the current process
  • Define the expected result
  • Agree the scope
Use case selected
02

Map what it needs

Identify the data, documents, systems, rules and people the solution depends on.

  • Existing systems
  • Available data
  • Business rules
  • Security requirements
Environment mapped
03

Build and validate

Develop the use case around the real conditions of your business and test whether it delivers what was agreed.

  • Real company context
  • Defined success criteria
  • Working proof of concept
PoC delivered
04

Decide what earns the next step

Take it further, add another use case, broaden the scope, or stop.

  • Go deeper
  • Go broader
  • Go beyond
You decide what scales

No company-wide programme required to find out whether one use case is worth pursuing.

Built for your environment.

Your infrastructure or Atomic-provided infrastructure

Run inside your own environment where required, or use infrastructure provided and operated by Atomic.

Data layer

Your data and systems

Documents, records, rules and tools already in place.

Solution layer

Atomic solution

Built or configured around the selected use case.

Process layer

Your business process

The result returns to the work where it is needed.

Your company data stays under the agreed controls and is never used to train public models.

One atom could start a chain reaction.

Go deeper

Take the same use case further.

Expand the scope, add more data, introduce additional steps or move closer to production.

Go broader

Apply the same approach to another use case or business function.

What starts in one team can become the basis for the next opportunity elsewhere.

Go beyond

Turn individual use cases into a wider Data & AI roadmap.

Once enough is proven, step back and decide where the larger opportunity lies.

Which HR workflow is worth proving first?

Start your journey