AI resume parsing and candidate screening buttons for Odoo Recruitment, powered by the LLM provider you choose. Built, installed, and supported by ECOSIRE. One-time license from $299.00 USD for Odoo 17, 18, 19 — includes 12 months of updates and support.

AI resume parsing and candidate screening buttons for Odoo Recruitment, powered by the LLM provider you choose. Built, installed, and supported by ECOSIRE.
No payment now. This sends a quote request to our team — we'll follow up by email with pricing and next steps.
Your recruiters open Odoo Recruitment, see 300 new applicants, and start copy-pasting from PDFs into applicant forms. That is the bottleneck this module removes. ECOSIRE builds a net-new Odoo add-on that layers AI directly into your existing hr.applicant workflow: a one-click "Parse Resume" button reads the attached PDF/DOC/DOCX, extracts structured data, and auto-populates the applicant form, while a "Screen vs. Job" button scores each candidate against the specific job position and posts a rationale to the chatter.
One-click 'Parse Resume' button on the hr.applicant form that reads the attached PDF, DOC, or DOCX from ir.attachment and extracts structured data
Structured extraction of work experience, education history, skills, certifications, languages, and contact details into discrete fields
AI candidate screening: a 'Screen vs. Job' action that scores each applicant against the specific hr.job position requirements
Screening score stored as a real numeric field (with an @api.depends compute for match band) so you can sort, filter, group by, and report on it
Auto-population of native applicant fields: name, email, phone, LinkedIn, expected salary hint, and a parsed skills summary
Provider abstraction service supporting Claude (Anthropic), OpenAI, Google Gemini, and self-hosted Ollama, selectable in Settings
This is not a generic apps.odoo.com download and never claims to be. It is a build-to-order engagement: we develop the module against your Odoo edition (Community or Enterprise, versions 17, 18, or 19), wire it to the LLM provider you choose, test it, deploy it, and hand you clean, documented source. Typical lead time is 2 to 4 weeks depending on scope and your provider decisions.
Technically, the module ships as a proper Odoo addon: a __manifest__.py declaring dependencies on hr_recruitment, new fields extending hr.applicant via models.Model, compute methods with @api.depends for derived screening scores, server actions and buttons defined in inherited XML/OWL views, security enforced through ir.model.access.csv and record rules so recruiters only see their own pipeline, and a provider-abstraction service so you can run Claude, OpenAI, Gemini, or a self-hosted Ollama model without vendor lock-in. Resume attachments already living in ir.attachment are read in place. Parsed output maps to real recruitment fields, and screening results are stored as structured data you can filter, group, and report on with standard QWeb reports.
Because you choose the provider, you control cost and data residency. Run Ollama on your own hardware for zero per-token cost and full on-prem privacy, or use a hosted API key for higher accuracy. Either way the AI logic sits behind one configurable service, so switching providers later is a settings change, not a rebuild. ECOSIRE handles the engineering, the security model, the deployment, and a support window after go-live.
Manages high-volume roles and spends hours manually reading resumes and keying data into Odoo. Wants one-click parsing and an at-a-glance screening score so the shortlist surfaces itself instead of being hand-built.
Owns the Odoo Recruitment process and needs consistent, auditable candidate evaluation. Values the stored screening rationale in chatter, per-job rubrics, and record rules that keep each recruiter scoped to their own pipeline.
Cares about where candidate data goes. Wants the option to run a self-hosted Ollama model on-prem for zero data egress, control API keys, and keep the AI layer behind one swappable service rather than a locked-in SaaS connector.
Processes candidates for many clients and needs speed plus provider cost control. Uses bulk parse/screen across batches and picks a cheaper or on-prem provider to keep per-candidate AI cost predictable.
Buy the license on ecosire.com and download the AI Recruitment & ATS (Resume Parse + Screen) module ZIP from your account dashboard.
Extract the ZIP into your Odoo custom addons folder on the server (or upload via Apps > Install from file on Odoo.sh / runbot).
Activate Developer Mode, open Apps, click Update Apps List, search for AI Recruitment & ATS (Resume Parse + Screen), and press Install.
Open the new menu, paste your ECOSIRE license key, connect any external credentials (Shopify, Amazon, Stripe, etc.), and save.
Run the built-in connection test, sync your first 10 records, and schedule the recurring cron. Contact support if anything fails.
| Criterion | ECOSIRE | Custom Build | Competitor | Odoo Native |
|---|---|---|---|---|
| AI resume parsing into Odoo applicant fields | Possible but you build the LLM integration, prompts, and field mapping yourself | Some offer parsing, often tied to one vendor's cloud API | ||
| AI screening/scoring against the specific job | You design the scoring logic and rubric from scratch | Rarely; usually keyword matching, not LLM reasoning with rationale | ||
| Choose your own LLM provider (Claude, OpenAI, Gemini, Ollama) | Only if you architect an abstraction layer yourself | Typically locked to the vendor's chosen provider/SaaS | ||
| On-prem / data-residency option (self-hosted Ollama) | Achievable with significant effort | Usually not; data goes to their cloud | ||
| Fits your Odoo version and edition (17/18/19, Community/Enterprise) | Depends on listing; version gaps common | |||
| Built, deployed, and supported for you with a support window | Your team owns all delivery and maintenance | License + limited vendor support; no bespoke build | ||
| Full documented source ownership and extensibility | Often obfuscated or license-restricted | |||
| Bulk parse and screen across a batch of applicants | You build the batch server action | Varies by product |
This is a build-to-order engagement, not an instant download. Typical lead time is 2 to 4 weeks depending on scope, your Odoo version/edition, and your chosen LLM provider. After purchase we run a short scoping call to confirm your Odoo version (17/18/19), edition, provider choice, and screening rubric, then develop, test, deploy to your instance, and train your team. You never get a claim of instant access from apps.odoo.com because we build this specifically for you.
Every engagement includes a defined post-launch support window (agreed in the SOW) covering bug fixes and reasonable adjustments to the parse/screen behavior. Because you receive full documented source and ownership, your team can maintain and extend it independently. We also offer optional ongoing support and version-migration retainers if you want us to keep the module current as you upgrade Odoo or change LLM providers.
You choose: Claude (Anthropic), OpenAI, Google Gemini, or a self-hosted Ollama model. The AI logic sits behind one provider-abstraction service, so switching later is a settings change, not a rebuild. If data residency matters, run Ollama on your own hardware for zero per-token cost and no data leaving your infrastructure. For hosted providers we can also mask or redact sensitive fields before text is sent.
Yes. We build against Odoo 17, 18, or 19, on Community or Enterprise. The module extends the standard hr_recruitment app via view inheritance and new fields on hr.applicant, so it fits your existing Recruitment workflow rather than replacing it. Tell us your exact version and edition at scoping and we target that build.
Accuracy depends on the provider and model you select and on resume quality. Rather than treat the score as a black box, the module posts the AI's rationale to the applicant chatter and stores extracted fields you can review and correct. Screening is a decision-support signal to help recruiters prioritize, not an automatic accept/reject. You define the scoring rubric (skill weights, must-have keywords, experience thresholds) so results match how your team actually hires.
No. The parse action is configured to populate empty fields and surface a review summary rather than blindly overwrite manual entries, and you approve the field-mapping behavior during scoping. Bulk actions are permission-gated via ir.model.access.csv and record rules so only authorized recruiters can run them, and every change is tracked in the standard Odoo chatter for auditability.
AI resume parsing and candidate screening buttons for Odoo Recruitment, powered by the LLM provider you choose. Built, installed, and supported by ECOSIRE.