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Enterprise AI services for marketing

From first workflow
to scaled operation.

Draft & Goal pairs agentic AI engineering with enterprise marketing expertise. We scope the work, connect your stack, encode brand and governance rules, launch with your team, and stay close after go-live.

Delivered with you. Never dropped off.

  • Time to value First workflow targeted in 30 days
  • Delivery model Named AI + marketing team
  • Ownership Your workflows, patterns, and IP
Trusted by marketing teams running at enterprise scale
La PosteDécathlonTotalEnergiesDelseyGrouponMatch GroupOmnes ÉducationTuro
Three ways we work with you

Launch. Extend. Operate.

Start with the engagement that matches where you are today. Every mode is designed to leave your team with a working system and more internal capability than it started with.

01 01 · Launch

Enterprise AI onboarding

Move your first governed marketing workflow into production.

We select the right first use case, configure your knowledge and integrations, set acceptance criteria, and launch alongside the people who will own it.

Best for

Teams moving from prompts, pilots, or backlog to a production operating workflow.

Prioritize

A workflow and ROI map grounded in business value, feasibility, and adoption.

Configure

Brand knowledge, data sources, models, integrations, roles, and approval gates.

Launch and enable

Controlled production runs, acceptance testing, owner training, and a working runbook.

Explore onboarding
02 02 · Extend

Implementation & integration engineering

Build the workflows and connections your operating model needs.

A forward-deployed engineer works with marketing, data, IT, security, and legal to extend the platform inside your real environment.

Best for

Teams with custom systems, migrations, complex governance, or a roadmap of additional workflows.

Production workflows

Reusable multi-agent workflows designed around the way your teams actually work.

Connectors and MCP

Custom integrations, tools, and knowledge access built, tested, and documented.

Migration and governance

Legacy automations rebuilt with permissions, human review, auditability, and monitoring.

Meet the engineering model
03 03 · Operate

Managed success & optimization

Keep quality, cost, adoption, and the roadmap moving after launch.

Your service layer scales with the plan—from standard support to a named success team, a shared channel, review cadence, and enterprise SLA.

Best for

Teams treating AI workflows as a production capability, not a one-off implementation project.

Workflow health

Quality, failures, usage, and costs reviewed against the definition of done.

Named context

People who know your workflows, stakeholders, constraints, and next priorities.

Scale roadmap

New use cases prioritized and proven patterns expanded across teams and markets.

See the operating cadence
Why Draft & Goal

AI engineering meets enterprise marketing operations.

The hard part is not generating an answer. It is turning a marketing process—with its systems, standards, approvals, economics, and exceptions—into a reliable operating workflow.

AI systems

Production-grade agentic engineering

We design for reliability, evaluation, permissions, observability, cost, and change—not just a compelling demo.

  • Multi-agent architecture and orchestration
  • Model selection, routing, and evaluations
  • Knowledge, retrieval, and data access
  • Connectors, APIs, webhooks, and MCP
  • Human review, audit trails, and monitoring
Marketing systems

Deep enterprise marketing context

We understand the workflows before we automate them, from the operating metric to the final approval and publishing step.

  • SEO and content supply chains
  • Campaign and demand operations
  • Localization and multi-market governance
  • Brand systems and approval chains
  • CRM, CMS, analytics, and reporting

One delivery team can hold both the technical architecture and the operating reality—so less gets lost between strategy, IT, and production.

Co-founder & CEO

Nabil Tayeb

10+ years in performance marketing and e-commerce · NextAI ’23 · Creative Destruction Lab ’24

Co-founder & CTO

Vincent Terrasi

Product, data, and AI leadership at OnCrawl, OVH, and Groupe M6 · 70,000+ learners trained

The 30-day onboarding plan

A concrete path to production—not a prolonged pilot.

The target is a governed workflow running on real inputs, with clear owners and acceptance criteria. Timing depends on access to data, systems, and enterprise review teams.

  1. 01
    Days 1–5

    Discover and prioritize

    Map the process, baseline the economics, identify risks, and select the first workflow by value and feasibility.

    • Opportunity map
    • ROI baseline
    • Definition of done
  2. 02
    Week 2

    Design the operating system

    Design the workflow, data access, brand knowledge, model policy, integrations, permissions, and approval path.

    • Solution design
    • Integration inventory
    • Governance matrix
  3. 03
    Week 3

    Build and validate

    Build the production workflow, test representative cases, tune quality, and validate human checkpoints with owners.

    • Working workflow
    • Acceptance tests
    • Review queue
  4. 04
    Week 4

    Launch and hand over

    Run controlled production, monitor the first executions, train owners, and document the operating cadence.

    • Production launch
    • Owner runbook
    • Optimization backlog
After launch

Improve what production teaches us.

Quality, usage, exceptions, model cost, and business results feed the next iteration and the roadmap for additional workflows.

See the full onboarding plan
White-glove after launch

A named team that stays close to the work.

Support is most useful when it has context. Higher service levels keep the people who know your environment connected to workflow health, adoption, and the next business priority.

Growth includes tailored onboarding and standard support. Agency adds guided onboarding and dedicated Slack. Enterprise adds a named success team, governance design, and an SLA.

Design my service plan
01 Shared channel

Context-rich support

Issues reach people who understand the workflow, its owners, and the systems around it.

02 Workflow reviews

Quality and cost optimization

Review failures, output quality, usage, model routing, and spend against operating targets.

03 Quarterly

Executive roadmap

Assess business value, adoption, and the next workflows worth launching or expanding.

04 Enterprise

Named team and SLA

Defined ownership, escalation path, response-time commitments, and governance support.

Proof in production

The workflow changes. The numbers follow.

These outcomes come from combining production software with the process design, data, approvals, and operating ownership around it.

TotalEnergies Workflow design · Content operations · Human approval

Thousands of SEO pages refreshed manually at four hours each became a governed content-refresh operation.

1,200% Productivity gain on SEO content
92% Reduction in annual content cost
24/day Articles, up from 2

“You can't imagine how much time I save by using Draft & Goal. The information is ready as soon as I open the dashboard.”

François Rommel · TotalEnergies
Read the case study
Turo Workflow architecture · Marketplace data · Scalable publishing

A marketplace content challenge became a repeatable programmatic workflow connected to real location and vehicle data.

~$1 Cost per page generated
10,000s Pages shipped
Hours Instead of months

“AI automation has enabled us to generate thousands of unique pages in record time, while boosting our SEO and considerably reducing costs.”

Julien Deneuville · Head of SEO, Turo
Read the case study
Service levels

Know what support surrounds the platform.

Every paid plan includes onboarding tailored to its scope. Higher tiers add a closer working channel, named context, governance design, and contractual response commitments.

Know what support surrounds the platform.
Service capability Growth Agency Enterprise
Production onboarding Tailored setup Guided White-glove
Primary support Email, docs, community Dedicated Slack Named success team
Governance design Scoped Scoped Included
Forward-deployed engineering Custom scoped
Service-level agreement Included
Roadmap reviews As needed As needed Quarterly

Final services, capacity, response times, and commercial terms are confirmed in your order form.

See plans and capacity
FAQ

The questions enterprise teams ask before launch.

How long does onboarding take?

The target is a first workflow in production within 30 days. The exact timeline depends on workflow scope, data and system access, and the timing of security, legal, and stakeholder reviews.

Who needs to participate from our team?

Most launches need a marketing process owner, a subject-matter expert, and the people who control relevant data, systems, security, or legal review. We keep their involvement focused around decisions, access, acceptance, and ownership.

What is a forward-deployed engineer?

An AI engineer who works directly with your marketing and technical teams to build production workflows, integrations, and governance inside your real environment—then documents and hands over what was built.

Who owns what gets built?

You do. Workflows, connectors, brand and knowledge configuration, documentation, and operating patterns built for your deployment stay in your workspace, subject to the terms in your order form.

What can extend the 30-day target?

The most common dependencies are unavailable APIs, delayed data access, custom security requirements, and stakeholder or procurement reviews. We identify these during discovery and make the critical path visible.

Is white-glove onboarding included in every plan?

Every production plan includes onboarding tailored to its scope. Agency adds guided onboarding and dedicated Slack support. Enterprise adds a named success team, governance design, and an SLA; forward-deployed engineering is scoped separately.

Can you work with our agency or systems integrator?

Yes. We can deploy alongside internal teams, agencies, or systems integrators, with clear ownership for workflow design, data, approvals, implementation, and ongoing operation.

Map your first workflow

Bring the workflow.
Leave with a path to production.

In 30 minutes, we'll identify the first workflow, map its systems and approvals, and outline a realistic route to production.