示意预览AI resume parsing and candidate screening buttons for Odoo Recruitment, powered by the LLM provider you choose.
Built, installed, and supported by ECOSIRE.
什么是 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. Built to order by ECOSIRE for Odoo 17, 18, 19 — indicative price from $999.00 USD; request a quote for a scoped proposal.
核心功能
按需定制，全程代劳
无需自行搭建——由 ECOSIRE 构建、安装并提供支持的可用应用。
- 1
您下单
以一次性构建价格开始。我们在启动时与您共同确定范围。
- 2
我们构建与安装
ECOSIRE 在您的 Odoo 上构建、配置并安装。
- 3
上线 + 支持
约一个工作周内上线，并包含两周上线支持。我们交付的代码中的缺陷免费修复。
技术规格
- Odoo 兼容性
- Odoo 17, Odoo 18, Odoo 19
- 版本
- 企业版和社区版
- 许可证
- 许可证需要确认
- Python 要求
- Python 3.10+
- 数据库
- PostgreSQL 12+
关于此产品
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.
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 one working week 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.
你得到什么
- 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
这是给谁的
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.
AI Recruitment & ATS (Resume Parse + Screen) 如何比较
| 标准 | 伊科西尔 | 定制建造 | 竞争对手 | Odoo 原生 |
|---|---|---|---|---|
| AI resume parsing into Odoo applicant fields | 包含 | Possible but you build the LLM integration, prompts, and field mapping yourself | Some offer parsing, often tied to one vendor's cloud API | 不包括在内 |
| AI screening/scoring against the specific job | 包含 | You design the scoring logic and rubric from scratch | Rarely; usually keyword matching, not LLM reasoning with rationale | 不包括在内 |
| Choose your own LLM provider (Claude, OpenAI, Gemini, Ollama) | 包含 | Only if you architect an abstraction layer yourself | Typically locked to the vendor's chosen provider/SaaS | 不包括在内 |
| On-prem / data-residency option (self-hosted Ollama) | 包含 | Achievable with significant effort | Usually not; data goes to their cloud | 不包括在内 |
| Fits your Odoo version and edition (17/18/19, Community/Enterprise) | 包含 | 包含 | Depends on listing; version gaps common | 包含 |
| Built, deployed, and supported for you with a support window | 包含 | Your team owns all delivery and maintenance | License + limited vendor support; no bespoke build | 不包括在内 |
| Full documented source ownership and extensibility | 包含 | 包含 | Often obfuscated or license-restricted | n/a — core app only |
| Bulk parse and screen across a batch of applicants | 包含 | You build the batch server action | Varies by product | 不包括在内 |
关于AI Recruitment & ATS的常见问题
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 one working week 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.
相关模块
AI Recruitment & ATS
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