Marketing teams want AI, agents, and automation. You’re the one who has to say yes, and who gets the call when a pipeline breaks. Alli runs the data connections, sets shared definitions, and lets AI act only within the permissions people already have. Your teams set the rules, and every run leaves a trail.
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With Alli, PMG built Nike's Global Media Data Foundation. Alli Datasources pulls in data from about 200 platforms and internal systems, the Alli Semantic Layer gives every market the same taxonomy and business logic, and Alli Alerts protects data quality. Daily feeds go straight into Nike's CRM, CDP, and MDM.
207Countries spanned
1000+Accounts across regions
PMG built the full launch, from research to creative to a full-funnel media plan, in six weeks. Underneath it, Alli Datasources brought 27 sources into one place and the Alli Semantic Layer gave every metric one shared definition.
6Weeks to Develop Launch Plan
54%Increase in Search Interest
With Alli, PMG defined the audience as ambitious innovators, from IT teams to the executives they report to, and created "The Cloud Is Yours," a cinematic anthem about the freedom secure cloud operations make possible. It ran across premium placements including The Wall Street Journal and Hulu.
7.2MMTargeted Impressions
4.3MMVideo Completions
Marketing runs on dozens of platforms, each with its own API, and each API changes. Somebody maintains the connectors. When one quietly breaks, every dashboard downstream is wrong until a person notices.
Then there’s AI. Marketing teams adopt tools on their own, credentials end up in chat windows, and costs are hard to see. The result is a handful of people running AI experiments while the rest of the business waits, and a security team that has reasons to be nervous.
You don’t need a longer list of tools. You need a foundation you can reason about, and a way to say yes without losing control.
Connectors break when platforms change. Engineering time goes to keeping pipes alive
Alli Datasources automates ingestion and handles API maintenance when platforms change
Teams define metrics their own way. Every report needs an explanation
Alli Semantic Layer defines KPIs and business logic once, with a consistent taxonomy across platforms
Signal loss from privacy changes. Conversion data goes missing
Alli Audience Gateway is managed server-side tracking: one integration sends first-party conversion signals to Meta, Google, TikTok, and Pinterest
AI tools appear without review. Credentials and costs spread unseen
Alli4u enables models person by person, tracks token use for each user, and locks down keys, tokens, and secrets
Agents need data access. Custom integrations for each one
Alli MCP Server lets AI agents call Alli tools within each user’s permissions, with no custom code
Automations run in the shadows. Nobody can say what ran, or who changed it
Alli Generative Workflows and Alli Apps carry credential management, role-based access, code verification, and audit trails
Alli is PMG’s operating system for business transformation, and for IT it works as a stack with a clear order. The data foundation comes first, because AI is only as reliable as what it reads. Enterprise AI controls who can use which model and which tool. Workflow automation carries repeat work, with the same permissions and an audit trail. Each layer relies on the one beneath it.
What changes for youConnections are managed, definitions are shared, and each number can be followed back to its source
See Alli for Data FoundationWhat changes for youPeople get models and agents inside existing permissions, and you can see who uses what
See Alli for Enterprise AIWhat changes for youTeams describe a job in plain language, it runs on a schedule, and you keep the credentials, access rules, and audit trail
See Alli for Workflow AutomationTwo adjacent pages help with the business side of the conversation. Alli for Self-Serve Answers shows what marketers do with the foundation once it’s in place. Alli for Measurement shows how finance relies on it.
Three illustrations of the work. They show how the products fit together, not results from a named client.
An ad platform renames fields and changes its reporting structure. In a hand-built pipeline, dashboards go quiet or wrong, and an engineer finds out from a marketer.
Datasources handles API maintenance as part of the service, so connections are updated as platforms change. Downstream, Alli Alerts can flag feed failures, so the team hears about problems in Slack.
Which sources are connected in the first place, and what quality checks you want on the data that flows through.
The analytics team wants an AI coding assistant to query marketing data and build dashboards. The last time a team did this, a token was pasted into a shared document.
MCP Server lets the assistant discover and call Alli tools, secured with OAuth 2.1 with PKCE. Requests carry each user’s authorization, so the agent can reach only what that person can. Teams decide which tools to enable, and read-only setups are possible.
Which tools are exposed, which users get access, and whether agents may take actions or only read.
A marketer builds a reporting automation that a dozen colleagues now rely on. Nobody in IT has seen it.
Alli4u gives the builder an approved workspace, with models enabled per user and secrets locked down. If the automation becomes an app, Alli Apps puts it through code verification and reviews, and records an audit trail on every deploy. Access is controlled by team or client.
Who can build, what needs review before it ships, and who can use what is built.
Built to scale your team’s judgment, not replace it.
Alli does the ingestion, the maintenance, and the routine runs. IT, data, and security teams decide what connects, who gets access, what gets reviewed, and what is allowed to run.
Connecting data. Automates ingestion and maintains connections
Approve sources, and set quality expectations
Defining the data. Applies shared definitions across tools and regions
Own the standards, and approve changes to them
Granting AI access. Enables models per user and tracks usage
Decide who gets which model, and review usage and cost
Connecting agents. Exposes Alli tools within existing permissions
Choose which tools are on, and whether any can write
Running automations. Runs scheduled workflows with audit trails
Review what ships, and investigate when something looks wrong
Each part of Alli carries the controls that fit what it does, and they all sit on the same permissions model. Agents act inside each user’s existing access, and generative models don’t make mapping or schema decisions in the data layer.
Start with the layer that is hurting most. Each entry point makes the next one safer.
| If your biggest problem is... | Start with | First step |
|---|---|---|
| Connectors that keep breaking | Datasources | Move your highest-maintenance sources onto managed ingestion |
| Metrics defined five ways | Semantic Layer | Define the shared KPIs, and map platform naming to one taxonomy |
| AI use you can’t see or control | Alli4u and MCP Server | Enable models for one pilot team, and expose a read-only set of Alli tools |
How Alli helps technical teams support marketing’s use of data and AI with control.
It’s a way of using Alli’s products together for the questions technical teams own: whether marketing data is reliable and maintained, how AI is used safely, and how automation is controlled. It draws on the Data Foundation, Enterprise AI, and Workflow Automation solutions, with your teams setting the access rules.
Alli MCP Server uses OAuth 2.1 with PKCE, forwards each user’s authorization with every request, and handles requests statelessly, so tokens aren’t stored between calls. Agents see only what the user behind them can see. Teams choose which tools are enabled, and read-only setups are possible.
Alli4u enables models user by user and tracks token usage for each person, so you can see who uses what and what it costs. It also locks down and syncs API keys, tokens, and secrets, and separates configurations by customer, business unit, or product line, so automations run against the right data.
Generative Workflows provides credential management, role-based access, and audit trails for every run. Alli Apps applies code verification, reviews, and audit trails to every deploy, with access controlled by team or client. Both leave a record your security team can inspect when something looks wrong.
Alli Datasources does, as part of the service. It automates ingestion from ad platforms, analytics, and first-party systems, and handles API maintenance when platforms change. Your engineers stay involved in choosing sources and setting quality expectations, but they stop spending cycles keeping connectors alive.
The Alli platform holds a current SOC 2 Type II report from an independent auditor, and our security program is aligned with the NIST Cybersecurity Framework (CSF). Request the report.
Alli is available to PMG clients. Technical, data, marketing, and finance teams work on the same platform PMG’s experts use, so permissions and definitions are consistent. Book a technical walkthrough to see the architecture with your own sources, models, and access rules.
Book a technical walkthrough and bring your security questions. We’ll show you how the data foundation is maintained, how agents stay inside permissions, and what the audit trail records. Alli is available to PMG clients.