Recruitment data fragments quickly
Candidates, jobs, clients, notes, documents, email, calls, tasks, and submissions become disconnected across tools.
AI-powered recruitment ATS and CRM
ATZ CRM: recruitment software shaped by the whole agency workflow.
ATZ CRM is an AI-powered recruitment ATS and CRM founded by Ayush Sharma. It brings candidate, job, client, business-development, communication, automation, and reporting workflows into one operating product for recruitment teams.
Founder relationship is user-confirmed. Product capabilities, a 30+ country footprint, screenshots, customer commentary, and review-platform presence are visible on the public ATZ CRM website; this page does not repeat unsupported conversion or productivity claims.
Users & market
Workflow & records
Operating constraints
ATZ CRM
Useful product
Reliable operations
Founder lessons
- Relationship
- Founded
- Ayush Sharma founded ATZ CRM; it is an owned product, not an Automiq client-logo claim.
- Public product footprint
- 30+ countries
- The current ATZ CRM homepage states that agencies use the product across more than 30 countries.
- Capterra profile
- 5.0 from 10 reviews
- Capterra displays ten moderated ATZ CRM reviews and a 5.0 overall rating as reviewed on 16 August 2026. Verify the live profile for the current count.
Evidence labels below distinguish public sources, founder confirmation, and records still pending.
Product interface
A current product surface buyers can inspect.
Screenshots come from the public product website and are shown as product evidence, not as an unrelated client deliverable.
Original market problem
The operating friction the product is designed around.
A credible product overview starts with user work and system failure—not a generic feature inventory.
Search does not understand recruiter intent
Keyword-only retrieval misses related skills, role context, career progression, and useful existing database candidates.
Client and candidate handoffs lose context
Sourcing, screening, submission, feedback, interviews, offers, and placement need one traceable history.
Target users
Who ATZ CRM is designed to serve.
The product organizes different responsibilities around shared operational state.
Recruitment agencies
Boutique and growing agencies coordinating candidates, jobs, clients, outreach, submissions, and placements.
Staffing and contract teams
Teams that also need timesheets, assignments, invoices, workforce records, and customer reporting.
Recruiters and business-development teams
People who need shared relationship history, tasks, pipelines, communication, and accountable next actions.
Core product modules
A complete workflow, not one isolated dashboard.
Current availability and commercial terms should always be checked on the live product website.
Candidate ATS and talent database
Profiles, resumes, notes, activities, search, parsing, deduplication, pipeline stages, and data ownership.
Jobs and recruitment pipeline
Requirements, owners, candidates, stage movement, tasks, interviews, feedback, offers, and placement context.
Client CRM and business development
Companies, contacts, opportunities, sequences, meetings, communication history, and relationship reporting.
Sourcing and outreach
Supported imports, contact context, email sequences, follow-up, templates, consent, and delivery visibility.
Submissions, portals, and job board
Candidate reports, client review, feedback loops, branded job publishing, and application intake.
Contract staffing and operations
Assignments, timesheets, invoices, workflow automation, reporting, administration, and permissions.
AI & automation
Intelligence bounded by product state and human authority.
The product surface and responsible engineering boundaries are separated from speculative AI claims.
Contextual candidate search
Search and retrieval use skills, experience, role context, and recruiter intent while leaving selection with the recruiter.
Candidate–job matching
Rank relevant profiles as decision support, with the underlying profile and job evidence available for review.
Parsing and summarisation
Turn resumes, calls, and recruitment records into structured fields or concise context with correction paths.
Assisted content and outreach
Draft job, candidate, and communication content inside approved workflows rather than acting as an autonomous hiring decision-maker.
System view
How the visible product workflows fit together.
This explanatory model helps buyers reason about the product without pretending to disclose its private infrastructure.
- Stage 01
Recruiter & stakeholder surfaces
- Recruiter workspace and administration
- Client portal, candidate intake, and job board
- Email, calling, calendar, and extension entry points
- Stage 02
Recruitment workflow
- Candidate, job, client, placement, and activity state
- Permissions, stages, tasks, sequences, and rules
- AI search, matching, extraction, and summaries
- Stage 03
Data & integrations
- Documents, communication, reporting, and search indexes
- Supported sourcing, email, calendar, telephony, and job channels
- Imports, APIs, webhooks, reconciliation, and audit history
- Stage 04
Product operations
- Tenant controls, onboarding, billing, support, and observability
- Model and workflow monitoring
- Release, recovery, and customer feedback loops
Integrations
Connected systems need ownership, reconciliation, and failure paths.
A connector is only useful when identities, source records, retries, exceptions, and support responsibility remain clear.
Email and calendar
Communication sync, templates, scheduling, activity history, deliverability, authorization, and account-level controls.
Calling and transcription
Supported calling, recording, transcription, summaries, consent handling, and searchable conversation context.
Sourcing and job channels
Candidate import, job publishing, applications, identity matching, duplicate handling, and source attribution.
Automation and APIs
Rules, webhooks, workflow integrations, exports, reporting, and governed access to connected business systems.
Architecture & scale considerations
What becomes important after real users arrive.
These concerns come from operating software over time, not from claiming a private stack or universal scale milestone.
Search quality and data hygiene
Recruitment intelligence depends on normalized profiles, duplicate control, current records, source traceability, and evaluation.
Permissions and privacy
Candidate and client data needs tenant isolation, role access, activity history, retention choices, and approved communication.
Communication reliability
Email, calling, scheduling, and automation need delivery state, retries, opt-out handling, and visible exceptions.
Adoption and support
Imports, setup, training, responsiveness, roadmap decisions, and reversible releases determine whether the product becomes daily infrastructure.
Evidence register
What is public, confirmed, or still pending.
Ratings, customer totals, performance claims, and badges are excluded unless the product-level source and usage permission are attached.
| Evidence | Published value | Status | What a buyer should infer |
|---|---|---|---|
| Relationship | Founded | founder confirmed | Ayush Sharma founded ATZ CRM; it is an owned product, not an Automiq client-logo claim. |
| Public product footprint | 30+ countries | public source | The current ATZ CRM homepage states that agencies use the product across more than 30 countries. |
| Capterra profile | 5.0 from 10 reviews | public source | Capterra displays ten moderated ATZ CRM reviews and a 5.0 overall rating as reviewed on 16 August 2026. Verify the live profile for the current count. |
Source links, where available, remain attached to the public product and case-study pages; a status label is not an independent verification claim.
Investment and timeline
Product history is evidence, not a pre-priced client estimate.
The time and investment used to create ATZ CRM do not predict a new engagement because users, integrations, assurance, migration, release responsibility, and evidence differ.
How is a new timeline estimated?
Automiq reviews the current workflow or product, defines a bounded production outcome, records dependencies and customer decisions, and sequences acceptance and release gates.
How is investment estimated?
Commercial scope follows the agreed milestone, disciplines, system access, data and integration work, quality controls, environments, handover, and continuing operating responsibility.
Operating lessons
What building and running the product taught.
The strongest credibility comes from the decisions and failure modes the team has had to understand over time.
One shared model beats disconnected features
Candidate, job, client, activity, and placement state must work as one system or every new feature creates reconciliation work.
AI must live inside recruiter review
Search, matching, extraction, and drafting are useful when the person can inspect context, correct output, and own the decision.
Imports are product experiences
Migration, mapping, deduplication, validation, and rollback affect trust as much as the first dashboard.
Support informs architecture
Customer questions expose ambiguous state, missing controls, performance bottlenecks, and the next valuable product decision.
Relevant technologies
Engineering options relevant to this class of product.
These links show Automiq capabilities and architecture choices buyers may need. They do not disclose or certify the product’s complete private stack.
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TypeScript
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PostgreSQL architecture, migration, and application development
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OpenAI
Custom OpenAI development for production systems
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AWS
AWS software and production AI development
Explore AWSRelated case study
The founder and engineering relationship, explained separately.
The case study focuses on context, decisions, operating challenges, evidence, and lessons rather than repeating this product overview.
Product visual
Founded by Ayush Sharma
ATZ CRM
Recruitment · B2B SaaS experience involving AI, Web app, Workflow automation, CRM integrations.
- Recruitment
- B2B SaaS
Questions, answered
ATZ CRM questions, answered
Direct answers about ownership, capabilities, evidence, AI responsibility, and how the experience relates to client work.
Is ATZ CRM an Automiq AI client project?
No. ATZ CRM is a SaaS product founded by Automiq AI founder Ayush Sharma. Automiq uses the product-operating experience as relevant context and labels the relationship explicitly.
What does ATZ CRM manage?
Its public product surface covers candidates, jobs, clients, sourcing, pipelines, outreach, calling, submissions, portals, contract-staffing workflows, automation, and reporting.
Does ATZ CRM use AI to make hiring decisions?
The product describes AI-assisted search, matching, parsing, summaries, and content. Recruiters and hiring stakeholders remain responsible for evaluation, communication, selection, and employment decisions.
Can Automiq build another recruitment platform?
Yes, when the work is original software for the buyer’s own users and market. ATZ CRM experience can inform workflow, data, integrations, AI controls, adoption, and operations without copying proprietary code.
Talk to the engineering team
Build an original product with an operator-led engineering team.
Bring your users, workflow, market, constraints, and desired outcome. We will apply the operating lessons without copying another product’s code or business logic.