For agencies, brands and ad-tech platforms · since 2013

All your ad data, cleaned up and put to work.

We pull your ad, store and attribution data into one database you own, clean it, build your dashboards and any custom data work you need, then add AI that spots problems and acts only within rules you approve.

Not a media agency: we give your PPC team one set of numbers, plus AI agents that analyze accounts, draft campaigns and adjust bids within rules you approve.

  1. 1Pullfrom every platform
  2. 2Storein a database you own
  3. 3Cleanone ROAS you agree on
  4. 4Dashboardsthat refresh themselves
  5. 5AI insightsproblems flagged early
  6. 6AI actionsbids & budgets, your rules

Works with

  • Amazon Ads
  • Walmart Connect
  • Shopify
  • Google Ads
  • Meta
  • TikTok
  • Attribution

+ Instacart, Criteo, Noon, Snapchat and other networks · every Amazon marketplace, from Amazon.ca to Amazon.ae and Amazon.com.au

Trusted by Tinuiti, BTR Media, Pixis, SellerFuse and Mau Brands · the data layer Tinuiti ran on as it grew to 3,500+ brands

Engineers reviewing code and dashboards in an open-plan office

How it works

From scattered ad data to AI that acts.

Six steps we run for agencies and brands. Build all six, or start with the one that hurts most.

Your warehouse
Scheduled · every 15 min to daily✦✦

01 · Pull

Every platform, pulled automatically.

Scheduled API jobs pull Amazon, Walmart, Google, Meta and TikTok, your Shopify store and your attribution tool. No CSV exports, no stale snapshots.

Your warehouseSnowflakeBigQueryRedshift
Reporting-readyfct_ad_spend_daily
  • Spend$48.2k
  • Revenue$127.7k
  • ROAS2.65
Cleanedstg_campaigns
  • ✓ One schema
  • ✓ USD
  • ✓ UTC
  • ✓ Deduped
Raw, kept foreverraw_ads_*
  • amazon_ads.json
  • meta_ads.csv
  • walmart.json
  • shopify_orders
🔒 Your cloud · your account · your keys

02 · Store

One place, and it's yours.

Everything lands in your own Snowflake, BigQuery or Redshift, in your cloud. Raw data is kept, so history can be rebuilt any time.

03/14/26£7401.2knull
→
2026-03-14USD 926.3012000
✓ tests passing

03 · Clean

Messy in, clean out.

Columns, currencies, time zones and attribution windows lined up into one model, with one ROAS rule you agree on. Tests catch what people miss.

PlatformAccountCampaignProductRetailerRegion
Blended ROAS by retailer
ROAS 2.65Refreshed 6:00 am

04 · Dashboards

Reports that run themselves.

Dashboards and client reports refresh on their own in Looker, Looker Studio, Power BI or Tableau, white-labeled for agencies.

AI
Meta ROAS −8% · frequency rising
Google CPC spike · 12 keywords
Amazon ACOS above target · 3 ASINs

05 · AI insights

AI that spots it first.

AI flags drops, waste and odd spikes before anyone opens a dashboard, writes the summary, and answers questions in plain English.

Your cap
↓ Bid −12%within your cap ✓
↑ Budget +$240/daywithin your cap ✓
⏸ Pause ad clusterneeds your OK
Every change logged · roll back anytime

06 · AI actions

AI that acts, within your rules.

Agents analyze accounts, draft new campaigns, move bids and budgets and pause waste inside caps and approval queues you set. Every change is logged and can be rolled back.

Custom work

Pipelines and dashboards are the start. The custom work is where it pays.

No two clients need the same thing. Once your data is clean and in one place, we build what your team asks for on top of it.

01

Custom metrics

Margin-adjusted ROAS, contribution margin by channel, TACoS by brand, new-to-brand by retailer. Whatever your finance team actually uses.

02

Client-specific views

Per-client rules, KPIs and white-label reports for agencies, without forking the pipeline for every account.

03

Data joined to your business

Inventory, margins, promotions, CRM and offline sales next to ad spend, for inventory-aware pacing and real profit.

04

Cleanup and reconciliation

Cross-network deduplication, restated conversions, currency and time-zone fixes, and the matching finance signs off on.

05

Forecasting and modeling

Budget forecasts, marketing mix models and incrementality analysis built on the same clean data.

06

Apps and tools on your data

Internal tools, client portals and product features, like the ad platform and creative studio we engineered for Pixis.

Tell us what you need built

Platforms

Ads, store and attribution data in one schema.

Every platform reports its own way: different columns, mixed currencies, four date formats in one table. We turn all of it into one model your team and your AI can trust.

Marketplaces & retail media

Our deepest platform

Amazon Ads, SP-API & AMC

Sponsored Ads, DSP, the Selling Partner API and Amazon Marketing Cloud, lined up across every marketplace. When Amazon changes a report, you get an alert, not a gap in your dashboards.

  • Sponsored Products, Brands & Display
  • Amazon DSP
  • SP-API sales, inventory & fees
  • Vendor Central (1P)
  • AMC queries & audiences
  • Every marketplace

Built for: Tinuiti, SellerFuse, Protego, Mau Brands

Amazon data in depth

Walmart Connect

Campaign, item and spend data pulled on a schedule, matched to the same model as Amazon so you can compare retailers like for like.

  • Sponsored Search
  • Item & keyword reports
  • Spend vs. item sales
  • Cross-retailer ROAS

Built for: BTR Media's retail media platform

Walmart data in depth

Also: other retail media networks like Instacart and Criteo.

Store

Shopify

Orders, revenue and customers, joined to ad spend so ROAS is based on real sales, not what each platform claims.

  • Orders & refunds
  • Customers & LTV
  • Products & margins
  • Discounts & shipping

Works alongside Triple Whale, Northbeam or your attribution tool.

Shopify data in depth

Search & social

Google Ads

Campaign, keyword and search-term data pulled through the API, with full history backfills.

Meta Ads

Audience and creative breakdowns, joined to the same spend model as every other channel.

TikTok Ads

Spend, impressions and conversions with TikTok's own attribution settings kept, ready for like-for-like comparisons.

Attribution

Your attribution platform

Attribution data joined in, so every channel is credited on one model instead of each platform claiming the same sale.

Warehouse

Your ad data warehouse

Snowflake, BigQuery or Redshift in your own cloud, modeled from raw to reporting-ready. CRM and finance data can join too.

Who it's for

For teams spending on more than one ad platform.

Three kinds of teams hire us. All of them are tired of stitching exports together before they can make a call.

For agency founders, ops, data & ad tech leads

Performance & retail media agencies

You run many client accounts across Amazon, Walmart, Google, Meta and TikTok, and analysts lose days to exports. We build one pipeline for every client, with per-client rules and white-label client reports, so strategists get numbers they can defend.

  • 120+ automations for Tinuiti across five ad platforms and marketplaces
  • 1 pipeline across every SellerFuse client account
  • 3 marketplaces in one pipeline and dashboard for BTR Media
For agencies
For VPs of Ops, heads of performance & ecommerce directors

Amazon, marketplace & CPG brands

You sell on Amazon, Walmart and Shopify, buy media on Google, Meta and TikTok, and still can't see true ROAS in one place. We join ad spend to real sales (retailer data for Amazon and Walmart, Shopify orders for your store), automate the reports, then let AI handle routine bid and budget moves within your rules.

  • 25% less reporting time for Mau Brands
  • 15% better campaign performance for Mau Brands
  • 4–6 wks to a first live pipeline
For brands
For product, engineering & data leads

Ad-tech & SaaS platforms

Integrations are your product. We build and maintain Amazon Ads API, SP-API, Walmart, Meta and TikTok integrations inside your codebase and sprints, multi-tenant and rate-limit safe, so your team gets back to the roadmap.

  • 30+ seller accounts on the SP-API platform we built for Protego
  • 2 Pixis products engineered with their team
  • 3 mo minimum for an embedded pod, then monthly
For ad-tech & SaaS

Trusted by teams that live in their ad data.

Agencies, retail media platforms and brands run their reporting, automation and AI on pipelines we built, including the data layer Tinuiti ran on as it grew from 35 to 3,500+ brands.

Case studies

Results for agencies and brands.

What one clean set of ad data did for these teams.

Before you ask

What working with us looks like.

Security & access

Everything runs in your cloud, under access you grant and can revoke. We use each platform's own API permissions with least privilege, keep credentials in your secrets manager, and log every change an agent makes. We sign your NDA before discovery and a DPA before any data access.

After launch

Choose a monthly plan where we run it, watch the alerts and fix breaks when a platform changes something, or a handover with docs, runbooks and a walkthrough. Either way, you're never stuck.

How pricing works

Every engagement is custom: pipelines, dashboards and the data work your team needs on top. We quote after a free 30-minute call, as a written scope with a fixed price, then an optional monthly plan. How pricing works

Working with your team

Agencies get one pipeline across every client account, per-client rules and white-label client reports. In-house data teams get work done in their own repo and dbt project, through their own code review.

How we build

An engineering team focused on ad data.

Engineering since 2013, with teams in Lahore, Sharjah, Bengaluru and Surrey, BC. Our focus: give agencies, brands and ad-tech platforms ad data they can trust, then put it to work.

FAQ

Common questions about ad data

Which platforms do you work with?

Amazon Ads (including SP-API and Amazon Marketing Cloud), Walmart Connect, Shopify, Google Ads, Meta and TikTok, plus attribution platforms. We also work with Instacart, Criteo and other retail media networks.

Do we have to build all six steps?

No. Start with the step that hurts most, often one pipeline and one dashboard. A focused single-source pipeline usually ships in 4–6 weeks. Multi-platform work typically runs 8–14 weeks, depending on how many sources, how much history and what reporting you need.

Why do Amazon reports keep breaking?

Amazon changes report schemas, throttles endpoints and retires fields with little notice. We build pipelines with schema-change detection, automatic retries and versioned staging, so a breaking change becomes an alert we fix, not a silent gap in your dashboards.

How do you get one ROAS across every platform?

We pull each platform through its API, not CSV exports, and clean it into one model. Revenue comes from the right place for each channel: retailer sales data for Amazon and Walmart, Shopify orders for your own store. Then one ROAS rule you agree on is applied everywhere, so your team, your dashboards and your AI all use the same number.

How do you handle different attribution windows?

Every platform credits sales differently: Amazon uses 7- or 14-day windows depending on the ad type, Meta defaults to 7-day click and 1-day view, and Amazon restates recent conversions after the fact. We keep each platform's own numbers and window, re-pull recent days when they restate, and show your attribution platform's model next to them. Your blended view uses one rule you choose, and it's labeled clearly.

What's the difference between AI insights and AI agents?

Insights tell you what changed and why: a ROAS drop, wasted spend, a spike worth a look. Agents go one step further and make the change, like moving a bid, shifting budget or pausing waste. Most agent actions are rules you approve, with AI summaries on top. Many teams start with insights and add agents later.

Can AI really change bids and budgets safely?

You choose how much control to hand over. Either you approve every change, or you approve the rules once (bid caps, budget limits, which accounts) and the agent acts only inside them. Every change is logged with the before and after, can be rolled back, and the agent stops if the data feed is late.

Who owns the data and the code?

You do. Everything runs in your cloud (AWS, GCP or Azure) and your warehouse (Snowflake, BigQuery or Redshift). Code, docs and runbooks are yours.

Do you only do pipelines and dashboards?

No. Pipelines and dashboards are the foundation. Most clients also ask for custom work on top: their own metrics, client-specific views, data joined to inventory and margins, forecasting, or internal tools and product features built on the data. We scope that with you.

Do you run our ad campaigns?

We're not a media-buying agency: our core is the data layer. But our AI agents do real account work on top of it. They analyze your accounts and show what to fix first, draft new campaigns, keywords and budgets from rules you set for your team to approve, and adjust bids and budgets within your limits. Your PPC team or agency stays in charge; the agents take the repetitive work off their plate.

What does it cost?

Every engagement is custom, so we quote after a free 30-minute call: a written scope and a fixed price before any work starts. What shapes it is how many platforms and accounts you run, how much history to backfill, the custom work you need, and whether we run it or hand it over. Your own cloud and warehouse usage is billed to you by your provider.

Who looks after it once it's live?

Your choice. We can run and monitor it for you on a monthly plan, fixing breaks when a platform changes something, or hand it to your team with docs, runbooks and a walkthrough. You don't need to hire a data engineer to work with us.

Bring us your messiest ad report.

Talk to an engineer who works in Amazon, Walmart, Shopify, Google, Meta and TikTok data every day. We'll tell you what we'd fix first.

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