AI Sales Assistant & Next-Best-Action (CRM Copilot)

Name: AI Sales Assistant & Next-Best-Action (CRM Copilot)
Brand: ECOSIRE
SKU: ai-sales-copilot

Recursos Principais

ML lead scoring on crm.lead: a model trained on your historical won/lost data writes a 0-100 conversion probability into a new stored field, recomputed via @api.depends when key inputs change

Next-best-action engine that recommends the single highest-impact step per opportunity (call now, send proposal, wait 3 days, re-assign, disqualify) and renders it in an OWL side panel on the lead form

AI-drafted follow-up emails generated per buyer persona and deal stage, pre-filled into the native Odoo composer (mail.compose.message) so reps review and send in one click

Conversation and email summarization that reads the mail.thread chatter and produces a short, structured recap of what has happened and what the prospect wants

Pipeline risk detection that flags stalled or slipping deals (no activity, overdue next_activity, stage age) with a plain-language reason

Forecast hints layered onto expected_revenue and probability, giving managers an AI-adjusted view of the pipeline alongside Odoo's native forecast

Persona and tone configuration so drafted copy matches your brand voice, industry and language, stored per company via ir.config_parameter

Pluggable LLM provider layer (OpenAI, Anthropic, Azure OpenAI or self-hosted) selected in Settings, with API keys held server-side and never exposed to the browser

Automated nightly re-scoring and risk sweeps via ir.cron, plus event-driven recompute through base.automation when a lead changes stage or receives a message

One-click 'Ask the Copilot' action on any lead for ad-hoc questions ('why is this deal at risk?', 'draft a re-engagement email') answered in context

Full audit trail: every AI request, prompt, model, token count and response is logged to a dedicated model for compliance and cost tracking

Role-scoped security via ir.model.access.csv and record rules so reps see AI suggestions only for their own opportunities, managers see the whole pipeline

Multi-language drafting that respects the lead's res.partner language, useful for teams selling across regions

Optional XML-RPC / JSON-RPC endpoints so an external tool or website form can request a score or a draft from the same engine

QWeb-rendered deal briefing report a manager can print or email before a pipeline review, summarizing top risks and recommended actions

Feito sob encomenda, pronto para você

Sem configuração por conta própria — um app funcional criado, instalado e com suporte da ECOSIRE.

Você faz o pedido

Comece com um preço único de desenvolvimento. Definimos o escopo com você no início.

Nós criamos e instalamos

A ECOSIRE cria, configura e instala no seu Odoo.

No ar + suporte

Você entra no ar em cerca de 2–4 semanas, com um período de suporte pós-lançamento.

Sobre este Produto

The AI Sales Assistant & Next-Best-Action module turns Odoo CRM into an AI-assisted selling engine. Instead of reps guessing which of 400 open opportunities to touch next, the copilot ranks the pipeline with an ML lead-scoring model trained on your own won/lost history, surfaces a concrete next-best-action on every crm.lead record, and drafts persona-aware follow-up emails your reps can send in one click. It reads the mail.thread chatter to summarize long conversations, flags at-risk deals before they slip, and injects forecast hints into your existing pipeline views.

This is a build-to-order module, not an instant apps.odoo.com download. ECOSIRE designs, builds, installs and supports it for your specific Odoo database. We extend crm.lead with new fields and @api.depends compute methods for the score and next-action, wire an LLM provider of your choice (OpenAI, Anthropic, Azure OpenAI or a self-hosted model) behind an ir.config_parameter-driven service layer, and expose everything through native Odoo views, an OWL side-panel widget, automated actions (ir.cron / base.automation) and QWeb-rendered summaries. Access is governed by ir.model.access.csv and record rules so a rep only ever sees and acts on their own pipeline, and every AI call is logged for auditability.

The module ships clean on Odoo 17, 18 and 19, works on both Community and Enterprise (Enterprise unlocks the richer forecasting and dashboard surfaces), and is delivered with source code, a deployment on your server, documentation, admin + sales-rep training, and a warranty support window. Because we build it against your data model, your sales stages and your tone-of-voice, the recommendations are grounded in how your team actually sells — not a generic template you have to bend your process around.

O que você ganha

Complete, commented Odoo module source (custom addon with __manifest__.py declaring dependencies on crm and mail) delivered to your repository, licensed for your use

Installation and configuration on your Odoo 17/18/19 environment (staging first, then production), including the LLM provider wiring and API-key setup

Initial ML lead-scoring model trained and validated against a snapshot of your own won/lost history, with the training approach documented

Security configuration: ir.model.access.csv entries and record rules mapped to your existing sales roles, reviewed with your admin

Admin documentation (settings, provider config, cron schedules, cost/audit log) plus a sales-rep quick-start guide for the copilot side panel and one-click drafting

Live training sessions: one for administrators and one for the sales team, recorded for future onboarding

A defined post-go-live support & warranty window covering bug fixes and adjustments, with an SLA agreed in your order

Prompt and persona templates tuned to your brand voice, handed over so you can edit tone and messaging yourself

Para quem é isso

VP of Sales / Sales Director

Wants a defensible way to focus the team on the deals most likely to close and to spot slipping opportunities before the forecast misses. Uses the risk flags, forecast hints and the QWeb deal-briefing report to run tighter pipeline reviews.

Sales Development & Account Reps

Spends too long deciding who to contact and rewriting the same follow-up emails. Relies on the next-best-action panel to prioritize the day and on one-click AI-drafted, persona-aware emails to move deals faster without leaving the Odoo lead form.

Revenue Operations / Odoo Administrator

Owns the CRM configuration, data quality and tooling budget. Values that the scoring model is trained on the company's own data, that LLM keys stay server-side, that every AI call is audit-logged for cost control, and that access is scoped by record rules.

Sales Enablement / Team Lead

Coaches reps and standardizes messaging. Uses the persona/tone templates and conversation summaries to keep outreach on-brand and to quickly get up to speed on any rep's deals during 1:1s.

Como AI Sales Assistant & Next-Best-Action (CRM Copilot) se compara

Critério	ECOSIRE	Construção personalizada	Concorrente
Time to a working solution	2-4 weeks, built, installed and validated on your database by ECOSIRE	Months of in-house dev, plus hiring ML/LLM skills you may not have	Fast to install but generic; still needs weeks of your own configuration
AI lead scoring trained on YOUR data	Yes — model trained on your own won/lost crm.lead history	Possible, but you build and maintain the whole ML pipeline	Rarely; usually rule-based points or a one-size-fits-all model
AI-drafted, persona-aware follow-up emails	Yes — pre-filled into the native composer, tuned to your brand voice	Only if you build the LLM integration and prompt tuning yourself	Sometimes via a bolt-on; tone and personas seldom match your team
Next-best-action recommendations	Yes — one concrete recommended step per opportunity in an OWL panel	Buildable but requires designing the whole recommendation logic	Uncommon; most stop at scoring, not prescriptive actions
Data & key control (server-side, audited, self-host option)	Keys server-side, every call audit-logged, self-hosted LLM optional	Depends entirely on how well your team implements it	Often routes data through the vendor's cloud with limited visibility
Ownership, source code & support	You receive the source, plus a warranty window and optional retainer	You own it but also own all maintenance and future Odoo migrations	Licensed per-user; you rarely get source and depend on their roadmap
Fit to your sales stages and process	Built around your pipeline, roles and record rules	Fully custom, at full custom cost and timeline	You bend your process to the app's assumptions

Perguntas frequentes sobre AI Sales Assistant & Next-Best-Action (CRM Copilot)

How long until the module is delivered, and is this an instant download?

This is a build-to-order module, not an instant apps.odoo.com download. After your order and a short scoping call, typical delivery is 2-4 weeks depending on how much of your won/lost history we train on and how custom your personas and provider setup are. We build and validate on a staging copy of your database first, then install on production. You will never be told to 'download and install it yourself' — ECOSIRE delivers it working.

What ongoing support and updates do I get after go-live?

Every order includes a post-go-live support & warranty window (agreed in your order) covering bug fixes and reasonable adjustments to prompts, scoring and personas. We keep the module compatible across the Odoo version you run (17, 18 or 19), and can provide a paid support/retainer plan for continued tuning, new features and migrations to future Odoo releases. Because you receive the source code, you are never locked out of your own module.

Does this work on Odoo Community or only Enterprise?

It runs on both. The core copilot — lead scoring, next-best-action, AI drafting, summarization and audit logging — works on Odoo Community 17/18/19. Odoo Enterprise unlocks the richer forecasting surfaces and dashboard widgets that build on Enterprise-only features. We confirm exactly what your edition supports during scoping.

Which AI/LLM does it use, and where do my data and API keys live?

The module has a pluggable provider layer — you choose OpenAI, Anthropic, Azure OpenAI, or a self-hosted model. API keys are stored server-side via ir.config_parameter and are never exposed to the browser. Every request is written to an audit log with model and token counts so you can track cost and review exactly what was sent. If data residency matters, we can wire it to a self-hosted model so prompts never leave your infrastructure.

How accurate is the lead scoring, and what data does it need?

The score is produced by a model trained on your own historical crm.lead won/lost outcomes, so it reflects how your business actually converts rather than a generic benchmark. Accuracy improves with the volume and quality of past data; during the build we validate the model on a held-out slice of your history and share the results honestly. We do not publish made-up accuracy percentages — the real number depends on your dataset, which we measure together.

Will it interfere with our existing CRM customizations or automations?

No. The module extends crm.lead with additive fields and compute methods and integrates through standard Odoo mechanisms — inherited views, base.automation, ir.cron and the native mail composer — rather than overwriting core behavior. We install to staging first and test against your existing customizations before touching production, and access is scoped with record rules so it only affects the pipeline data each user is already allowed to see.

AI Sales Assistant & Next-Best-Action (CRM Copilot)

An LLM copilot inside Odoo CRM that scores leads, drafts follow-ups and recommends the next best action. Built-to-order by ECOSIRE.

ML lead scoring on crm.lead: a model trained on your historical won/lost data writes a 0-100 conversion probability into a new stored field, recomputed via @api.depends when key inputs change

AI-drafted follow-up emails generated per buyer persona and deal stage, pre-filled into the native Odoo composer (mail.compose.message) so reps review and send in one click

Conversation and email summarization that reads the mail.thread chatter and produces a short, structured recap of what has happened and what the prospect wants

Recursos Principais