Data you can trust.
Tools your team will use.
Teams don't use tools they don't trust, and they don't trust numbers that change or can't be explained. Alli starts with a deterministic, governed data foundation, so the same inputs produce the same numbers every time. AI works on top of it alongside your people. Experts frame the questions, shape the strategy, and approve what goes live, and the AI scales their expertise so teams deliver results faster and more consistently than they could alone.
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Why does trust in data decide whether teams use a tool?
A tool is only as useful as the confidence people have in what it tells them. When the numbers in a dashboard don't match the numbers in a platform, or change between Monday and Friday, people stop relying on them. They go back to spreadsheets, double-check everything by hand, or argue about whose number is right. The tool stays licensed and goes unused.
AI raises the stakes. An AI assistant built on data that teams already doubt gives answers they'll doubt too, only faster and in more places. Accurate, consistent, traceable data is the first requirement, because if teams don't trust the data, they won't use anything built on it.
See how Alli proves impact| When teams don't trust the data | When teams do | |
|---|---|---|
| What people do with a report | Re-check it in a spreadsheet | Use it to make the decision |
| Meetings | Spent debating whose number is right | Spent deciding what to do next |
| How people treat AI answers | Verify everything by hand, or ignore them | Act on them, and check the source when it matters |
| Adoption of new tools | Stalls after the pilot | Spreads from team to team |
| Cost of an error | Quietly spreads into every report | Found and fixed at the source |
If teams don't trust the data, they won't use the tool. Everything else follows from that.
What makes data trustworthy in Alli?
Three things: the data is deterministic, every number traces back to its source, and every product uses the same definitions. A deterministic data foundation is a data layer where the same inputs always produce the same outputs. Every mapping, transformation, and definition is written down explicitly, version-controlled, and traceable. Nothing in it guesses, infers, or generates. A metric means the same thing today as it did last quarter.
In Alli, that foundation is the Alli Data pillar. Alli Datasources brings data in through governed ingestion pipelines. Alli Semantic Layer defines every KPI once and, through Categorizations, maps platform naming into one taxonomy. Changes are deployed through controlled platform workflows, with people accountable at each step. The result is a set of numbers teams can check, repeat, and defend in a meeting.
Deterministic
The same inputs produce the same outputs.
Version-controlled
Every change to a mapping or definition is tracked.
Traceable
Every number links back to its source.
Reproducible
Any result can be rebuilt and checked.
| Deterministic data layer | Generative AI in the data layer | |
|---|---|---|
| Same input, same output | Yes, every time | Not guaranteed. Results can vary between runs |
| How mappings and definitions are made | Written explicitly and reviewed by people | Inferred or generated by a model |
| Version control | Every change is tracked | Hard to track what changed and why |
| Lineage | Every number traces back to its source | Lineage can break where the model made a choice |
| Debugging and audit | Straightforward | Errors can be hard to detect and explain |
| Effect on everything downstream | Stable and consistent | Small inconsistencies spread into every report and agent |
Why isn't there generative AI in Alli's data layer?
Because the data layer is what every other part of the platform trusts. Ingestion pipelines, categorizations, and semantic models are foundational assets. If a generative model were allowed to create mappings, transform data, or make schema decisions there, it could introduce inconsistencies that are hard to detect, debug, and audit, and those inconsistencies would quietly flow into every dashboard, plan, and agent above it.
Keeping the foundation deterministic isn't a limitation. It's what lets the intelligent products above it move quickly. Monitoring tools like Alli Alerts read the governed data to flag anomalies, but they don't change it.
No silent drift
Definitions don't change unless a person changes them on purpose.
Errors you can find
When something looks wrong, the team can trace where it came from.
Audits you can pass
Finance, legal, and security teams can see how every number was produced.
AI you can rely on
Agents built on a stable foundation give stable answers.
How does trusted data make Alli's AI more reliable?
Because the data underneath is consistent and traceable, the AI on top can be too. AI runs in the products across Alli Intelligence, Alli Planning, and Alli Activate. There, agents research, reason, plan, produce, and monitor, and every one of them reads from the same governed foundation, the same definitions, and the same business context. That's why the output of one product is consistent with the next. When Ask Alli and Alli Creative Insights describe the same campaign, they agree, because they're reading the same numbers.
| Layer | What happens there | Examples |
|---|---|---|
| Alli Data (deterministic foundation) | Data is connected, defined, and governed. No generative AI. | Alli Datasources, Alli Semantic Layer, Alli Audience Gateway |
| Alli Intelligence | Agents answer questions, find patterns, and explain what's driving results | Ask Alli, Alli Creative Insights, Alli Business Insights |
| Alli Planning | Agents build personas, model scenarios, score creative, and build dashboards | Alli Audience Planner, Alli Scenario Planner, Alli Creative Labs, Alli Generative Dashboards |
| Alli Activate | Agents build workflows, produce creative, and connect outside AI tools | Alli Generative Workflows, Alli Creative Studio, Alli4u, Alli Apps, Alli MCP Server |
How does agentic orchestration work in Alli?
Agentic orchestration means AI agents in different products pass signals and hand work to each other, instead of each tool working alone. Above the governed foundation, Alli behaves like one connected system. A signal in one product becomes research in another, a plan in a third, and an action in a fourth. People are part of every step: they direct the research, shape the plan, and approve the action.
- 01SignalAlli detects it
- 02ResearchAgent + analyst
- 03RecommendationAgent + strategist
- 04ApprovalOwner signs off
- 05ActionGoes live
- 06ResultFeeds back into the data
A creative refresh
Alli Creative Insights flags that a top-performing ad is starting to fatigue. A creative strategist asks Ask Alli which attributes drove its results and decides which hook to change. Alli Creative Studio prepares refreshed versions from the approved template.
The brand owner reviews and approves them before they go live.
A pacing issue
Alli Alerts flags a campaign pacing ahead of plan. A workflow the media team built in Alli Generative Workflows pulls the context and drafts a recommended budget shift to Slack.
The media lead weighs it against what they know about the market and decides whether to make the change.
How do people and AI work together in Alli?
Built to amplify expertise, not replace it.
Alli's AI isn't built to take people out of the work. It's built to scale what they know. Your experts are involved throughout: they frame the questions in Intelligence, shape the strategy in Planning, and approve what goes live in Activate. AI handles the volume, speed, and repetition in between, so teams deliver results faster and more consistently than they could alone.
| Stage | What AI does | What people do |
|---|---|---|
| Understand Alli Intelligence | Pulls and summarizes data, finds patterns, flags anomalies and fatigue | Decide which questions matter, judge what an answer means for the brand and market |
| Plan Alli Planning | Builds personas, models budget scenarios, scores creative, builds dashboards | Set the strategy, weigh the tradeoffs, choose the plan |
| Produce Alli Activate | Produces creative versions, builds workflows from a prompt, prepares recommendations | Define the brand rules and templates, decide what gets automated, review the output |
| Activate Alli Activate | Queues the change, the launch, or the delivery | Approve every decision that commits budget, launches a campaign, or ships creative |
| Learn Back to Alli Data | Feeds results back into the governed foundation | Decide what the results mean for the next plan |
| Access Alli MCP Server, Alli4u | Calls Alli tools within each user's permissions | Set what each person and agent is allowed to see and do |
How is access controlled across Alli?
Trust isn't one feature. Each part of Alli carries the controls that fit what it does, and they all sit on the same permissions model.
| Area | Controls |
|---|---|
| Data foundation | Governed ingestion, version-controlled definitions, lineage, and controlled deployment workflows |
| Client data separation | Dedicated Alli environments for proprietary data, audiences, and playbooks, with segregated teams for competing accounts |
| Generative Workflows | Credential management, role-based access, and audit trails for every run |
| Creative Studio | Approval workflows, version control, brand rules, and legal copy by market |
| Alli4u | Models enabled user by user, token usage tracked per person, and API keys and secrets locked down |
| Alli Apps | Code verification, reviews, and audit trails on every deploy, with access controlled by team or client |
| Alli MCP Server | OAuth 2.1 with PKCE, token forwarding, and stateless requests, so agents act within existing permissions |
Is Alli independently audited for security?
Yes. 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).
Security and IT teams can request the SOC 2 Type II report and our security documentation under NDA.
Request security documentation| Standard | Status |
|---|---|
| SOC 2 Type II | Current report covering the Alli platform, issued by an independent auditor. Available under NDA. |
| NIST Cybersecurity Framework (CSF) | Security program aligned with the framework |
| Security documentation | Available to security and IT teams under NDA |
How does Alli compare to other approaches to AI?
Most teams use AI in one of two ways today: a general-purpose assistant working from exported files, or AI features added to individual tools. Both can be useful. Neither gives every team consistent, governed answers.
| General AI assistants on exports | AI features in separate tools | Alli | |
|---|---|---|---|
| What the AI reads | Whatever file someone uploads | That tool's own slice of data | One governed foundation shared by every product |
| Consistency across answers | Varies by file and prompt | Varies by tool | Products agree because they read the same numbers |
| Definitions | None | Each tool's own | Defined once in Alli Semantic Layer |
| Traceability | Hard to check | Limited to the tool | Every number traces back to its source |
| Role of people | Up to the user | Varies | People lead every step, with approval built in before budget is committed or anything goes live |
| Access control | Personal accounts | Per tool | Shared permissions model across the platform |
In production, not a pilot
of PMG clients use Alli's agentic products in their day-to-day work
These systems aren't a demo. Teams use them every day to plan campaigns, build audiences, produce creative, buy media, and prove impact. The controls described on this page are running client work right now.
What should you ask before trusting a platform with your data?
Whatever platform you choose, these questions show how much your team can rely on its data and its AI.
Does the same question get the same answer twice?
Why it matters: If the data layer isn't deterministic, results can drift without anyone noticing.
Can every number be traced back to its source?
Why it matters: Without lineage, nobody can check or defend an AI answer.
Where are business definitions stored, and who changes them?
Why it matters: If each tool defines "revenue" its own way, AI answers will conflict.
Do different AI features read from the same data?
Why it matters: If not, two tools can give you two different answers.
Where are your people in the loop?
Why it matters: Experts should shape the questions and the strategy, and budget, launches, and creative should not go live without a person's sign-off.
How are agent permissions controlled?
Why it matters: Agents should act within the same access rules as the people using them.
What's logged?
Why it matters: Every run, change, and deploy should leave an audit trail.
Is the platform independently audited?
Why it matters: An independent audit checks that security controls work in practice, over time. The Alli platform holds a current SOC 2 Type II report, available to security and IT teams under NDA.
The ideas behind data you can trust
- What is a deterministic data foundation?A data layer where the same inputs always produce the same outputs, with every mapping and definition explicit, version-controlled, and traceable.
- What is governed AI?AI that runs on governed data, within defined permissions, with audit trails and human approval, so its answers and actions can be checked and trusted.
- What are AI guardrails?The controls that keep AI working inside safe, approved limits: what data it can see, what it can do, what is logged, and what needs a person's sign-off.
- What is data governance?The rules, roles, and controls that decide how data is defined, accessed, changed, and checked, so people can trust and use it safely.
Data You Can Trust FAQ
How Alli keeps its data consistent, its AI grounded, and people at the center of the work, so teams trust it enough to use it.
Why does data trust matter for AI adoption?
Teams only use tools they trust, and they only trust numbers that stay consistent and can be explained. If people doubt the data, they double-check everything or stop using the tool, and AI built on that data inherits the doubt. Accurate, traceable data comes first because everything else depends on it.
What is a deterministic data foundation?
A deterministic data foundation is a data layer where the same inputs always produce the same outputs. Mappings, transformations, and definitions are explicit, version-controlled, and traceable to their source, and nothing is guessed or generated. In Alli, that's the Data pillar, including Alli Datasources and Alli Semantic Layer.
Why doesn't Alli use generative AI in its data layer?
Generative AI can introduce mappings, transformations, or schema decisions that are hard to detect, debug, and audit. In the data layer, those errors would spread into every report and agent above it. Keeping that layer deterministic gives every AI product a stable, traceable foundation to work from.
Where does AI run in Alli?
AI runs in the products across Alli Intelligence, Alli Planning, and Alli Activate, such as Ask Alli, Creative Insights, Audience Planner, Scenario Planner, Creative Studio, and Generative Workflows. Agents there research, reason, plan, produce, and monitor, and all of them read from the same governed data foundation.
How does Alli reduce AI hallucinations?
Alli's AI answers from governed business data and shared definitions, not from general training data or uploaded files. Every number traces back to its source, so answers can be checked. Because every product reads the same foundation, two products describing the same campaign give consistent answers instead of competing ones.
Where are people involved when Alli uses AI?
Throughout. People frame the questions in Intelligence, shape and choose the strategy in Planning, and approve every decision that commits budget, launches a campaign, or ships creative in Activate. AI handles the research, analysis, drafting, and production in between, scaling their expertise so teams get results faster and more consistently.
What is agentic orchestration?
Agentic orchestration means AI agents in different products pass signals and hand work to one another, rather than each tool working alone. In Alli, a fatigue signal in Creative Insights can lead to refreshed versions in Creative Studio, with a brand owner approving them before they go live.
How does Alli keep different clients' data separate?
Proprietary data, audience segments, and strategic playbooks are kept in dedicated Alli environments. For brands in competing categories, PMG also uses segregated teams with no personnel overlap and strict confidentiality protocols. Access within each environment follows role-based permissions, so people and agents only see the data they're cleared to use.
Can AI agents outside Alli access our data?
Only through Alli MCP Server, and only within existing permissions. It 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. Outside agents see the same governed data, and only what that user is allowed to see.
Is Alli SOC 2 compliant?
Yes. 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). Security and IT teams can request the report and security documentation under NDA.
Does Alli's AI replace people?
No. Alli's AI is built to amplify expertise, not replace it. It takes on the volume, speed, and repetition, like pulling data, modeling scenarios, and producing versions, so experts spend their time on judgment, strategy, and creative decisions. Teams deliver results faster and more consistently than they could on their own.
Keep exploring why teams choose Alli
Built by PMG
The 15+ year story behind Alli, built by the practitioners who use it every day.
Read the story behind AlliThe Alli Platform Explained
How Alli connects, governs, and activates your data across four pillars.
See how the Alli platform worksMeasurable Growth
How Alli proves impact and shows where the next dollar should go.
See how Alli proves impactNumbers your whole team will stand behind.
Book a walkthrough and we'll show you how an answer in Alli traces back to its source, how your experts guide the work at every step, and why finance, legal, and security teams can sign off on it.