Clean, organise and maintain existing candidate records so recruiters can find the right profiles, trust key fields and spend less time correcting database admin. Rudrriv can support agreed cleanup, duplicate review, standardisation, tagging, segmentation and record maintenance across your defined recruitment workflow.
Standard delivery: 5–7 working days. Final timing and price depend on record volume, data quality, field rules and access method.
| Candidate | Role Family | Location | Status |
|---|---|---|---|
| A. Sharma | Data Engineering | Pune | Ready |
| M. Lewis | Customer Success | London | Review |
| J. Santos | Finance | São Paulo | Active |
| K. Nguyen | Software | Singapore | Duplicate? |
Pricing is structured around a defined batch because record volume, data condition, field rules and manual interpretation are the main cost drivers. The $49 entry plan covers a focused, useful cleanup rather than a token task.
Tell us the approximate record volume, where the data sits and the main quality problems. We can confirm the right batch, exclusions and delivery expectation before work starts.
A recruitment database loses value when records are inconsistent, duplicated or difficult to search. Candidate database management is most useful when the problem is data usability rather than a lack of candidates.
Repeated profiles, old contact details and inconsistent statuses can create wasted recruiter effort and unreliable pipeline views.
Different job titles, locations, skills and source labels make filtering harder even when the candidate information is already present.
Records without consistent tags, role families or status values can turn an existing database into a manual search exercise.
The buying decision is simpler when the boundary is clear: database management improves the usability of candidate information you already hold or are authorised to process.
Choose this service when your immediate need is controlled record maintenance.
These needs go beyond straightforward database maintenance and should be confirmed separately.
Candidate records are not ordinary rows. Two records can look similar while representing different people, and a single candidate can have multiple applications or historical interactions. That is why duplicate treatment should use explicit rules and an exception path.
The exact matching rule should be agreed before processing begins. A typical controlled approach separates clear matches from uncertain cases.
Recruiters search by concepts such as role family, skills, location, seniority and availability. Database management becomes more valuable when those concepts use a consistent, customer-approved taxonomy instead of uncontrolled free text.
These fields are examples of useful classification areas. Rudrriv should apply only the fields and values agreed for your database rather than inventing a new recruitment taxonomy without approval.
The workflow is designed around defined rules, controlled changes and clear exceptions rather than broad, untraceable edits.
Confirm record volume, source, goals, fields and exclusions.
Agree duplicate logic, taxonomy, status values and protected fields.
Validate files or approved access and preserve key identifiers.
Clean, standardise, tag and flag records within approved rules.
Check the batch and separate exceptions needing customer decisions.
Return agreed outputs, exceptions and completion information.
Good database work depends on more than the data file itself. Clear rules prevent unnecessary rework and reduce the risk of inconsistent interpretation.
Quality control should focus on consistency, record integrity and transparent exception handling. The service is not intended to guess missing recruitment information or silently redesign your data model.
The service can be scoped around common recruitment-data formats and existing systems. Direct system work depends on the access method you approve; no specific ATS partnership or integration is implied.
These are practical situations where recruitment teams often need a finite, clearly controlled data-maintenance project.
Normalise records after high-volume hiring activity before the database is reused for future roles.
Clean fields, flag duplicates and structure records before moving data to another recruitment system.
Improve tags and statuses so recruiters can search an existing candidate pool more consistently.
Prepare inherited or fragmented candidate records before a broader recruitment operations engagement begins.
Candidate databases can contain personal information. Customers should provide only data they are authorised to process and define the applicable handling requirements for the project. Rudrriv should not infer a legal basis, retention period or regulatory requirement on the customer’s behalf.
Answers to the scope, pricing, inputs, turnaround and data-handling questions that typically affect a buying decision.
It is the structured maintenance of recruitment records so candidate information is organised, searchable and usable. Work can include cleanup, duplicate review, field standardisation, tagging, segmentation, status updates and exception logging under agreed rules.
No. This service focuses on candidate records already available to your recruitment team. New candidate sourcing, outreach, screening or end-to-end recruitment should be scoped separately.
The scope can cover records held in an ATS, recruitment CRM, spreadsheet export or another agreed repository, subject to access, file quality, record volume and your data-handling rules.
Duplicate handling follows agreed matching rules. Clear matches can be flagged or processed according to the approved workflow, while uncertain matches should be placed in an exception list rather than merged automatically.
Yes, where the required taxonomy and field rules are supplied or agreed. Typical fields include role family, skills, location, seniority, source labels and status values.
Not by default. Standard plans work within the existing agreed structure. New fields, workflow redesign, integrations, automations or system configuration require separate confirmation and may need custom scope.
Provide the in-scope data or approved access method, field definitions, duplicate rules, taxonomy or tagging guidance, status logic, retention restrictions and any records or fields that must not be changed.
Depending on scope, handoff can include the updated data set or completed system updates, an exception list for records needing customer decisions and a concise completion summary.
The standard delivery window is 5–7 working days. Larger record volumes, inconsistent source data, complex duplicate rules, missing field definitions or delayed access can extend the timeline.
The entry plan covers a focused cleanup of up to 250 existing candidate records with agreed field standardisation and duplicate flagging. Larger volumes or deeper classification require a larger or custom scope.
Record volume, number of fields, data quality, duplicate complexity, taxonomy depth, source-file count, access requirements, manual interpretation, exception volume and ongoing cadence all affect price.
Yes. CSV, XLSX or agreed spreadsheet workflows can be suitable for batch cleanup when identifiers, field mapping and output format are confirmed before work begins.
They can be referenced for agreed field completion or validation. Large-scale parsing, extraction or enrichment may require custom scope depending on file volume and quality.
Plan-based review rounds correct work against agreed rules. They do not introduce a new taxonomy, redesign the database or add a materially larger record set after work has started.
Provide only data you are authorised to process and define the applicable access, retention and handling rules. Do not put highly sensitive candidate data in the initial enquiry.
Yes, as custom scope when update frequency, record volumes, workflow, responsibilities, access method and service boundaries can be defined clearly.
Describe the current problem and approximate scope. Do not include candidate personal data in this first enquiry; we can confirm the project workflow after scope review.
We will review the requirement, confirm the appropriate service option and clarify pricing, inputs and delivery expectations.
