Quikstack, on the Snowflake AI Data Cloud
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Quikstack, on the Snowflake AI Data Cloud

The marketing data foundation your AI agents need

Quikstack is an accelerated custom data stack for advertising, campaign, and conversion data. It deploys into your own Snowflake account with sources already modeled, definitions already agreed, and access already governed for the AI agents you build on the same layer.

Book a walkthrough See how the data flows
20+ years in enterprise data 1000+ projects delivered 600+ customers Select Snowflake partner
The decision

Do you buy a platform, or build one?

Both routes are well understood. So are their costs. Quikstack takes what each does well and leaves the rest.

Option one

Buy a marketing analytics platform

Switch it on, connect a few sources, get dashboards this quarter.

What you get

  • Fast time to first report
  • No engineering team needed

What it costs you

  • Questions limited to what the vendor built
  • Your data in their tool, every connector a line item
  • Not built for your agents to read from
Option two

Build a custom stack from scratch

Assign a data team, pick the tools, model everything yourself.

What you get

  • Full ownership of data and models
  • Scales to any source or question

What it costs you

  • Months before a trustworthy number
  • An architect, an engineering team, and a long modeling debate
  • Reporting stays manual meanwhile
Quikstack

An accelerated custom stack on Snowflake. AI ready.

The speed of buying a platform with the ownership and scale of building your own. The model library, semantic layer, and governance ship into your Snowflake account already done, so you start where a custom build would finish.

1
Takes the speed of buyingSources modeled, KPIs defined, access set up. Live in days, not quarters.
2
Takes the scale of buildingYour account, your models, your tools. Add sources without asking a vendor.
3
You own it, and the roadmapThe data, models, and account are yours. No vendor decides which questions you can ask next.
How it works

Every source lands once. Every report, app, and agent reads from one layer.

Data lands in your Snowflake account, gets modeled and given business meaning, and passes through one set of access rules on its way out to people and agents.

Ad platforms and clickstream data flow into Snowflake with dbt models, then a semantic and knowledge layer with governance, then out to dashboards, custom apps, AI agents, and Teams or Slack. Quikstack foundation Consumption * ingest modeled Ad platforms Clickstream and CRM Google Ads, Meta, DV360, LinkedIn, TikTok GA4, app events, web, Salesforce, HubSpot Snowflake AI Data Cloud Your account. Raw landing, curated marts, lineage. dbt models Semantic and knowledge Metrics defined once. Documents and entities alongside. Governance Row-level policy and audit. One rulebook for people and agents. Dashboards Custom app AI agents Teams / Slack Your reports, any tool Analyze, act, extend Snowflake Intelligence, Claude, ChatGPT, or your own agents Ask and act in the chat

Sources

Ad platformsClickstream and CRM
↓

Snowflake AI Data Cloud, your account

Raw landingdbt modelsCurated martsLineage
↓

Semantic and knowledge

Metrics defined onceDocuments and entities alongside

Governance

Row-level policyAuditOne rulebook for people and agents
↓

Consumption *

DashboardsCustom appAI agentsTeams / Slack

* The consumption layer is scoped separately from the foundation. Snowflake Intelligence works on the semantic layer as delivered.

Built with Airbyte dbt Ingestion and modeling, open and swappable.
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Why Snowflake

A robust data foundation for data, analytics and AI.

Snowflake puts data, analytics, and AI workloads on one secure, governed platform. Storage and compute scale independently, so you pay for performance when workloads grow and pay less when they do not. Data is shared and accessed in place rather than copied between systems, and new use cases are built on the data you already have.

Independent compute and storage

Optimize cost and performance independently.

Elastic scaling

Scale with demand.

Built-in governance

Secure data by design.

AI-ready

Cortex, Snowflake Intelligence, and more.

What you get

The data modeling is finished before your kickoff meeting.

That is where the speed comes from. A custom build spends its first months designing the architecture and modeling the sources. Quikstack arrives with both done, so the project starts at the point a custom build would reach a quarter in.

Weeks from kickoff
0510152025 Project kickoff Custom build 14 to 25 weeks Architecture, then modeling, then the first trusted report Already done Pre-built dbt models and a ready architecture Quikstack live 4 to 10 weeks Connect your sources, tune the KPIs, go live Work already done before you sign

Not just speed. You also get:

Who it's for

Three people usually sit in this decision. Quikstack has an answer for each.

CMO, VP Marketing, VP Marketing Analytics

You own the budget and the buy-versus-build call.

You get cross-channel numbers your team trusts in days, on a platform the rest of the business can standardize on, and a foundation your AI initiatives can start on instead of waiting for.

It's time to talk ifa reporting platform is up for renewal, a custom build was scoped and then stalled, or someone asked for an AI agent over marketing data and there is nothing solid to point it at.
CDO, VP Data, Head of Data Platform

You own platform standards and sign off on the Snowflake footprint.

Marketing lands on Snowflake as a governed data asset instead of buying around IT. Layered modeling, lineage, and access rules are in the deployment, not bolted on later, and agents go through the same door people do.

It's time to talk ifyou already run Snowflake but marketing data has not landed there, it landed raw and unmodeled, or two teams keep presenting conflicting spend numbers.
Analytics manager, BI head

You absorb the reconciliation pain every week.

The model library does the harmonization you have been doing by hand. Your time moves from pipeline maintenance to analysis, and the semantic layer you would have written yourself is already there for your reports and your agents.

It's time to talk ifyou have been asked to make a chatbot or agent answer marketing questions and you know the definitions underneath are not ready.
What it sets up

Usable, meaningful, actionable. One stack covers all three.

Foundation

Make data usable

Every ad, web, CRM, and document source lands in your Snowflake account in a structure that is already agreed. Pipelines you do not have to design.

Meaning

Make data meaningful

Spend, CAC, ROAS, and conversions defined once in a semantic layer, with documents and relationships alongside. The contract that reports and agents both read from.

Action

Make data actionable

Snowflake Intelligence answers plain-English questions on the semantic layer from day one. Agents in Slack or Teams, custom apps, and actions back to the ad platforms build on the same foundation and are scoped as their own phase.

Pricing

One price to get the foundation live. Then it scales with you.

The base plan covers the Quikstack foundation described above, deployed into your Snowflake account. Anything on the consumption side is scoped with you as a custom plan.

Base plan
Starts from $15,000one-time implementation

The accelerated custom stack for up to 10 data sources: modeled, governed, and handed over in your account.

See what the base plan includesHide details
  • Deployment into your Snowflake account, or a new one we set up with you
  • Up to 10 data sources across advertising, clickstream, and CRM, modeled with the dbt library
  • Raw, curated, and business-ready layers with lineage and tests
  • Semantic layer with your KPIs defined once: spend, CAC, ROAS, conversions
  • Governance: role and row-level access, audit
  • Snowflake Intelligence enabled on the semantic layer
  • Handover, documentation, and a post go-live check-in
Start with the base plan
Custom plan
Talk to us

For teams that want the consumption layer built, more sources, or an ongoing partner.

See what a custom plan can coverHide details
  • Additional sources, markets, or business units
  • AI agents on the governed layer: Claude, ChatGPT, or your own, with MCP access
  • Agents inside Teams or Slack that answer and act
  • Custom apps and dashboards on top of the semantic layer
  • Actions back to the ad platforms with human approval
  • Managed optimization and Snowflake cost management after go-live
Scope a custom plan

Prices exclude Snowflake consumption credits, which you pay Snowflake directly on your own account. Base plan covers up to 10 data sources; more are scoped under a custom plan.

See your own ad data reconciled before you decide anything.

Bring exports from two or three platforms. We will walk through how they land, where they disagree, what the governed layer looks like for your team, and what an agent can answer from it.

Book a walkthrough Email sales@decisionfoundry.com

A 45-minute walkthrough covers

  • How your current sources map to the model library
  • Where cross-channel numbers will disagree, and how they get settled
  • Deployment into your Snowflake account, or a new one
  • Your reporting tools and AI agents connected to the same layer
  • What the first weeks look like, and what happens after go-live