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簡単な事実
- 価格
- $299.00 USD
- Odoo のバージョン
- 17, 18, 19
- セットアップ時間
- 20160分
- ライセンス
- ワンタイム永続
- 言語
- 11 言語
一回購入
AI Recruitment & ATS (Resume Parse + Screen)
AI resume parsing and candidate screening buttons for Odoo Recruitment, powered by the LLM provider you choose. Built, installed, and supported by ECOSIRE.
$299.00USD
今すぐのお支払いはありません。これはチームへの見積もり依頼を送信します。価格と次のステップをメールでご案内します。
主な機能
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
AI rationale posted to the applicant chatter (mail.thread) so every score has an auditable, human-readable justification
Bulk parse and bulk screen from the applicant list view, so a full batch of new applicants is processed in one action
Configurable scoring rubric per job or globally: weight skills, experience years, education, and must-have keywords
Automated action / server action hook so parsing can fire automatically when a new applicant is created from the website or email alias
ir.model.access.csv plus record rules restricting AI actions and results to authorized recruiters and hiring managers
Redaction / privacy option to strip or mask sensitive fields before text is sent to a hosted LLM (or force on-prem Ollama for full data residency)
Works across Odoo Community and Enterprise on versions 17, 18, and 19 with edition-appropriate view inheritance
Optional XML-RPC/JSON-RPC exposure so external tools or your careers site can trigger parsing programmatically
この製品について
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.
AI Recruitment & ATS (Resume Parse + Screen)を選ぶ理由
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.
得られるもの
- Complete, commented Odoo module source (Python models, XML/OWL views, security CSV, __manifest__.py) delivered as a versioned addon for your Odoo 17, 18, or 19 instance
- Provider configuration for your chosen LLM (Claude, OpenAI, Gemini, or Ollama), including secure API key handling via Odoo system parameters or environment config
- Installation and deployment on your instance (or a deploy runbook if you self-host), with the module installed and smoke-tested against real sample resumes
- Security model implementation: ir.model.access.csv access rights and record rules reviewed with you before go-live
- Admin and recruiter documentation covering configuration, the parse/screen workflow, and the scoring rubric setup
- A live training session (recorded) for your TA team plus a short admin walkthrough for changing providers or rubrics
- A defined post-launch support window (bug fixes and adjustments) with response commitments agreed in the SOW
- Source ownership and a handover so your team can maintain, extend, or re-deploy the module independently
これは誰のためのものですか
In-house recruiter / TA lead drowning in applicants
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.
HR operations manager standardizing hiring
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.
IT / Odoo administrator with data-governance duties
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.
Staffing agency owner scaling placements
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.
インストールの概要
ECOSIREからダウンロード
ecosire.com でライセンスを購入し、アカウント ダッシュボードから AI Recruitment & ATS (Resume Parse + Screen) モジュールの ZIP をダウンロードします。
Odoo にアップロードする
ZIP をサーバー上の Odoo カスタム アドオン フォルダーに抽出します (または、[アプリ] > [Odoo.sh / runbot のファイルからインストール] を介してアップロードします)。
モジュールをインストールする
開発者モードをアクティブにし、アプリを開き、「アプリリストの更新」をクリックして、「AI Recruitment & ATS (Resume Parse + Screen)」を検索し、「インストール」を押します。
設定を構成する
新しいメニューを開き、ECOSIRE ライセンス キーを貼り付け、外部認証情報 (Shopify、Amazon、Stripe など) を接続して保存します。
検証して公開する
組み込みの接続テストを実行し、最初の 10 レコードを同期し、定期的な cron をスケジュールします。何か問題が発生した場合はサポートにお問い合わせください。
AI Recruitment & ATS (Resume Parse + Screen) の比較方法
| 基準 | エコシエール | カスタムビルド | 競合他社 | オドゥー ネイティブ |
|---|---|---|---|---|
| AI resume parsing into Odoo applicant fields | 付属 | 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 | 付属 | 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) | 付属 | 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) | 付属 | Achievable with significant effort | Usually not; data goes to their cloud | |
| Fits your Odoo version and edition (17/18/19, Community/Enterprise) | 付属 | 付属 | Depends on listing; version gaps common | |
| Built, deployed, and supported for you with a support window | 付属 | Your team owns all delivery and maintenance | License + limited vendor support; no bespoke build | |
| Full documented source ownership and extensibility | 付属 | 付属 | Often obfuscated or license-restricted | |
| Bulk parse and screen across a batch of applicants | 付属 | You build the batch server action | Varies by product |
AI Recruitment & ATS (Resume Parse + Screen) に関するよくある質問
How long until the module is delivered, and what happens after I buy?
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.
What support and updates are included after go-live?
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.
Which LLM providers can it use, and do I need to send data to the cloud?
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.
Does this work with my Odoo version and edition?
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.
How accurate is the parsing and screening, and can I trust the scores?
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.
Will parsing overwrite data my recruiters already entered?
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.
関連モジュール
見積もりを依頼
AI Recruitment & ATS (Resume Parse + Screen)
AI resume parsing and candidate screening buttons for Odoo Recruitment, powered by the LLM provider you choose. Built, installed, and supported by ECOSIRE.
- 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