Now booking · next kickoff in ~2 weeks 4–6 week engagements

Your AI is only as useful as the data it can reach.

We connect your apps, pull the data into one clean place, and make it usable.

Starts at $15K Build time 4–6 wks Quote Fixed at kickoff Ownership 100% yours
See if it fits — 30 min, no slides → See how it works

If your business runs on it, we can pull from it. A few common examples:

Shopify Klaviyo Meta Ads Stripe NetSuite HubSpot Salesforce + your warehouse, internal tools, anything else with an API

No prep · no slides 30-min working session Walk away with a clear plan

$80M ARR running on a foundation we shipped
24+ Sources connected in one engagement
4–6wks Build to handoff, fixed quote
100% Yours — code, data, AWS account
Why pipelines · the analogy

AI is the car. Your data pipelines are the roads.

A brand-new car is useless if it can only drive on a handful of pre-paved highways. That's what off-the-shelf AI gives you: twenty supported connectors, maybe thirty — and nothing for the system of record that actually runs your business.

A pipeline is the road network. We lay the roads from your apps, your databases, your spreadsheets, your internal tools — into one place you own. Now the car can actually go somewhere. And you're not at the mercy of whether ChatGPT or Claude decides to support your stack next quarter.

Off-the-shelf AI · 3 exits

The car with a tiny highway.

Whatever's in the vendor's connector list, and nothing else. Your business lives somewhere off the map.

GDRIVE GMAIL NOTION your CRM (unreachable) your orders DB (unreachable) support tickets (unreachable) ad platforms (unreachable)
Your pipeline · the whole map

The car with actual roads — to everywhere you do business.

CRM, orders, tickets, ads, billing, your internal DB, that one spreadsheet. All reachable. All owned by you.

YOUR PIPELINE CRM Ad platforms Orders DB Billing Support tickets Internal DB Spreadsheets Internal tools
The missing piece You can't buy this off the counter. Every business has different apps, different data, and different questions worth answering. A pipeline has to be built — once — to fit you. Then it keeps working, quietly, for everyone on the team.
Built at scale

Different industries. Same shape underneath.

The pattern is repeatable — that’s the whole point. These are the businesses already running on it.

Case study DTC · Supplements
Live · production

How a $80M-ARR supplement brand stopped reconciling spreadsheets.

Shopify, Klaviyo, Meta, Stripe, NetSuite, Gorgias, plus a long tail of operational tools — pulled into one clean foundation. Now feeds the daily ops report and an AI assistant grounded on real orders, spend, inventory, and support volume.

The fight that ended

“Triple Whale said one CAC, Northbeam said another, Meta Ads Manager said a third. The Monday meeting was always about which number was right — never about what to do next. Now it’s one number. The foundation is the tiebreaker.”

Our weekly KPI review used to be a Slack scavenger hunt. Now the numbers are in one place and the meeting is about strategy, not which spreadsheet is right.
Director of Ops DTC supplement brand · 24 sources connected
12+ Industries shipped
  • DTC e-commerce
  • Multi-site medical
  • Real estate & brokerage
  • Financial services
  • SaaS analytics
  • Construction & field ops
  • + several covered by NDA we can’t list
The bet

Different industries. Different sources. Same shape underneath.

If your business has data living in too many places to answer one question fast — you’re already inside the pattern. We’ve built it before. We’ll build yours next.

01The offer

One fixed package. Crystal-clear.

No "it depends." No discovery retainer. Here's exactly what you get, what it costs, and what it runs on. Keep scrolling for the details, the timeline, and the FAQ.

The Package · 4–6 weeks

Your operational data, connected and ready for AI.

Your systems of record, pulled together into one clean, production-grade data foundation in your own AWS account. You own all of it.

Starting at $15,000 one-time build

Most builds land $15K–$30K depending on sources and stack — you'll leave the call with a fixed quote, not an estimate.

What this replacesThe build costs less than three months of the data hire you'd otherwise need. A junior data analyst runs $120–150K/year fully loaded. A real data engineer is $180–220K. The foundation does that job — connections, monitoring, definitions, AI integration — for a fraction of one year's salary, and runs for years.

Our promise. By the end of week 2, you'll see live data from your three priority systems flowing into one place. If we don't get there, you get a full refund — no questions, no clawback on what we've shipped.
What you get
Deliverables
  • 10 data sources connected — your CRM, billing, support, ads, ops tools, finance
  • 5 reports & dashboards built to your priority questions
  • 1 production-grade workflow — AI assistant, finance/ops automation, or weekly leadership report (your call)
  • Source code, schemas, and docs in a Git repo you control
Where it runs
  • Your AWS account. No vendor cloud, no SaaS dashboard. You own the storage, credentials, and access.
  • Best-in-class data stack — the same tooling serious data teams use, AI-ready out of the box (Claude, ChatGPT, Copilot, or your own model).

Production-grade means alerting on every connection, change-tracked in Git, retries when an upstream API misbehaves — the boring infrastructure that keeps it running at 3am. See the full architecture →

You own everything. No seat fees. No data hostage. Walk away any time and it keeps running.
Reserve a kickoff slot → Pay the kickoff deposit → Read the sample engagement agreement first
02What we connect

Whatever runs your business — we connect it.

Every business has its own operational stack. Here's a cross-section: CRMs, billing, support, ads, ops tools, finance. If your system has an API or a database, we can connect it. If we haven't seen yours, we'll build a custom connection in a week or two.

What counts as a "source"? One place data comes from — a SaaS platform like Shopify, a SharePoint site, a Google Drive folder, your internal database, that one spreadsheet in your finance lead's downloads.

200+ Connector types shipped in production

Across e-commerce, fintech, healthcare, real estate, internal tooling — every engagement adds to the library.

~1wk To build a custom connector when we haven’t seen one before

Legacy DBs, SFTP drops, internal APIs — the gnarly stuff doesn’t stop the build.

A cross-section of stacks we connect to

The categories live below — your specific tools probably aren’t listed but they fit one of these.

CRM Salesforce · HubSpot · Pipedrive
Billing & finance Stripe · Chargebee · QuickBooks
Ads & growth Google · Meta · LinkedIn Ads
Support Zendesk · Intercom · Freshdesk
Project & ops Jira · Asana · Linear · Monday
Your product’s DB Postgres · MySQL · Mongo · BigQuery
ERP NetSuite · Sage · Xero
Commerce & ops Shopify · WMS · ShipBob · 3PL
+ everything else SharePoint · GDrive · SFTP · webhooks · custom APIs
The moat

Custom Python connectors. Where off-the-shelf tools tap out.

Legacy SQL Server. A daily SFTP drop of CSVs. A bespoke ERP written in 2003. A webhook nobody wrote a connector for. We don’t tell you “that’s not supported” — we write the connector. That’s the whole point of a custom build versus buying a managed-connector tool.

REST API GraphQL Webhooks Direct DB SFTP / files Custom wrappers
For builders

Are you the engineer being asked to evaluate this?

Skip the marketing tour. Read the opinionated architecture, the foundation layer, how we think about agents, and what we deliberately skip.

Read the technical breakdown →
03Under the hood

One pipeline, end to end. From the apps you already use, to AI that finally answers.

No black box. Your apps in. AI-ready data out. Five stages, fully managed — you see the result, we own the plumbing.

YOUR APPS ONE CLEAN FOUNDATION FINALLY USABLE Shopify orders Klaviyo email Meta Ads ad spend Gorgias support Stripe payments Your data foundation organized · clean · ready to use raw data — kept safe ready-to-use tables one source of truth AI assistants that know your business Weekly reports numbers everyone agrees on Automations running on real data

The five stages, expanded ↓

01

Source

The systems already running your business.

  • shopify · stripe · netsuite
  • hubspot · zendesk · postgres
  • + 30 more connectors
connected
02

Ingest

Reliable, incremental, never falls behind.

  • cdc · webhooks · scheduled
  • schema drift handled
  • retry · alert · backfill
every 5 min
03

Model

Joined, deduped, typed, tested.

  • dbt · sql · python
  • 140+ models, version-controlled
  • tests on every column
1.2M rows / day
04

Govern

Defined once. Documented. Trusted.

  • metrics layer · lineage
  • access · pii masking
  • audit log · row-level rules
one source of truth
05

Serve

AI, dashboards, agents — all answering from the same truth.

  • chat · bi · webhooks · sdk
  • cited responses, every time
  • governed semantic layer
responding · 18ms p50
Tooling AWS · Custom Python connectors · dbt · Dagster · Snowflake · OpenAI · LangGraph
Where it runs Your cloud or ours · SOC2 vendors · keys you control
What you own Every model, every prompt, every connection. We hand it over.
04Real examples

Once your data's in one place, you can finally get real answers.

These are real questions we hear every week from business owners. Once the plumbing is there, any of them takes seconds instead of days.

You Why did our customer acquisition cost jump last month?
Your AI, now grounded CAC went from $180 to $240 in March. Paid spend across Google and LinkedIn was up 22%, but qualified pipeline from those channels only grew 4%. The drop is concentrated in one campaign — Enterprise Q1 Retarget — where cost-per-qualified-lead doubled. Outbound-sourced CAC held steady.
Sources HubSpot · Google Ads · LinkedIn Ads · Stripe
You Which accounts are showing churn signals this month?
Your AI, now grounded Seven accounts worth $184k in ARR are flashing yellow — usage down more than 30% over 60 days, support tickets trending up, and their champion hasn't logged in for two weeks. Three are up for renewal in the next 45 days. Two have CSM meetings scheduled; the other five are unowned. Want me to draft the outreach?
Sources Salesforce · your product DB · Zendesk
You Which parts of the business are running hot — and which aren't?
Your AI, now grounded Implementation team: 94% utilization, four weeks behind — needs relief. Support: tickets on one product area are 2× the average, 60% are "how do I use this?" — an onboarding gap, not a bug. Sales: pipeline coverage is healthy, but enterprise-deal conversion slipped 8 points.
Sources Jira · Zendesk · HubSpot · your HRIS
You Give me a clean picture of the business this month.
Your AI, now grounded Revenue is $2.14M MTD, tracking +8% vs. plan. New logos: 12 (plan 15). Net retention: 108%. CAC drifted up 9% — mostly paid spend. Gross margin held at 74%. Biggest risk: three enterprise renewals in the next 30 days at a combined $112k ARR. Biggest tailwind: product-qualified leads up 31% after last month's release.
Sources Salesforce · Stripe · NetSuite · product DB · Google Ads
05The difference

A week in your business, both ways.

The same questions come up every week. Here's what they look like without a data foundation — and with one.

Without a data foundation
With one
Monday morning number
Your ops lead exports four CSVs, reconciles them in a sheet, sends it at 11am. It disagrees with the one finance sent earlier.
Auto-generated Monday report hits your inbox at 7am. Same numbers every team is looking at. No one prepped it.
A question from the CEO
Slack thread. Four people loop in. The analyst is on PTO. You get an answer Thursday, caveated.
You type the question. You get an answer in under a minute, with the sources shown.
Your AI tools
Great at writing emails. Useless for running the business. Your team quietly stopped opening them.
Actually knows your orders, ad spend, subs, support. Pulls real numbers with real citations.
Automations
Run on screenshots and luck. Break silently. Someone discovers it a month later.
Run on the same clean data your reports use. You get alerted the minute something goes sideways.
Onboarding a new hire
"Here are the 12 tools. Good luck figuring out which numbers to trust." Takes them a month to be useful.
One clean view. One set of numbers. They're contributing in week one.
Seeing yourself on the left side of that picture?

Most businesses we talk to are one week of setup away from the right side.

See if it fits → See the offer
06The boring details that matter

The four things that separate a real build from a demo.

The Offer card lists the headline deliverables. These four are the operator-grade details — invisible on launch day, felt every day after.

01

A priority map of your stack

The apps and data worth tackling first, ranked by impact and effort. You approve it before we build anything — no scope creep, no surprise sources.

02

Agreed-upon definitions

What counts as a "new customer"? An "active subscription"? Locked down once so every team — and the AI — uses the same numbers.

03

Alerts when something breaks

You know before your team does if a source is down or data is going stale. No silent failures. No Monday-morning surprises in the leadership report.

04

Plain-English documentation

What's connected, what the numbers mean, what the gaps are. Written for humans — not a 200-page wiki nobody reads.

Illustrative What your existing AI tools become — not a UI we build

The AI tools you already use, now grounded on your real data.

We don’t build you a custom chat UI. You keep using Claude, ChatGPT, Cursor, Copilot — whatever your team already pays for. The foundation we build connects them to your real warehouse, so every answer is cited from a source table instead of guessed from last quarter’s PDFs. No hallucinations. No “based on the documents you uploaded.” And because the foundation keeps the history the SaaS tools drop, the AI can look back across years to find correlations no human would think to query. The exchange below uses fabricated numbers and a made-up company; your data and source list would be your own.

Cited every answer Sub-second on warm data Your warehouse · your auth
Works with Claude · ChatGPT · Cursor · Copilot · any MCP-compatible client
Claude · grounded on Acme Co’s foundation illustrative example
You
What were our top 3 SKUs by gross margin this month?
Assistant

Through Apr 26, your top 3 SKUs by gross margin:

#SKURevenueMargin
1Velour Throw Set$48,21062.4%
2Linen Duvet (Queen)$39,84058.1%
3Aroma Diffuser Refill$27,56071.8%
shopify.orders netsuite.cogs shopify.products queried 03:14 UTC · 12ms
You
Why is Aroma Refill margin so high?
Assistant

Two effects compounding:

  • No fulfillment cost overhead. Refills ship for $0.40 vs. $14 on the device unit.
  • Supplier renegotiation in March. NetSuite COGS shows unit cost dropped $7.20 → $5.90.
netsuite.cogs shopify.shipping_costs queried 03:14 UTC · 18ms
What this means Every answer points to the source table. No hallucinations, no "based on the documents you uploaded" — your real warehouse, your real numbers.
07Timeline

Four to six weeks, with real progress every week.

No black box. No giant discovery doc. You see working data and real results inside the first two weeks — and check in with us every step.

Phase
Week 1
Week 2
Week 3
Week 4
Week 5
Week 6
Plan
priority map
Connect
your apps
Organize
clean it up
Activate
ship workflows
08Is this for you?

Built for business owners who know AI matters — but know their data is a mess.

This is for you if...

  • Your business runs on a growing pile of SaaS apps.
  • You're doing real volume — real orders, real customers, real revenue.
  • You want AI that actually knows your business, not the internet.
  • Your team is tired of copy-paste work and arguing about whose number is right.
  • You want a practical start — not a nine-month rebuild before anything's useful.

This probably isn't for you if...

  • You just want a chatbot glued onto your FAQ page.
  • Your key tools have no exports or integrations at all.
  • You're pre-revenue and aren't sure what data you'll need yet.
  • You want everything modeled perfectly before showing anyone a result.
09Why now

Everyone bought AI. The ones winning are the ones whose AI can read their business.

You can wait. Or you can be the company everyone else spends next year trying to catch.

now 6 months 18 months value wait it out Start now compounding lead

The shift is already visible in the market. The teams pulling ahead aren't the ones paying for fancier AI — they all bought the same tools you did. They're the ones whose AI can actually answer questions from their own orders, ad spend, support, and finance.

You're sitting on years of data. The question isn't whether AI can unlock it — it can. The question is whether yours can reach the data that matters. Today, for most businesses, it can't.

And the data you’re not capturing today is gone in twelve months. Most ad-platform APIs (Meta, Google, TikTok) only return the last 365 days. The campaign that worked great in February of last year? If you didn’t capture it then, you can’t resurrect it now. Your foundation keeps the history that the SaaS tools quietly drop.

Most teams see the build pay back within a quarter — and 5–10× the cost in year one. Through hires you don't make, ops hours you reclaim, ad spend you stop wasting, and the AI tools you already pay for finally being useful. None of that is upside. It's what the foundation actually delivers — and it compounds every quarter you keep it running.

5–10×
Year-one return

What most teams see in the first twelve months — through avoided hires, reclaimed ops hours, ad spend the AI helps you stop wasting, and the AI tools you already pay for finally being useful.

  • Pays back in ≤ 1 quarter for most teams
  • Compounds quarterly while it keeps running
  • One-time build · low monthly run-rate
10Who's behind this

The person you'd actually be working with. Just one.

No sales rep, no junior implementer, no offshore handoff. You email me, you get me on the call, you work with me end-to-end.

Hunter Sneed, founder of Pipelines for AI
Hunter Sneed Founder · Pipelines for AI

For the last decade I've built data infrastructure for businesses that can't afford for it to break — Fortune 500 financial services, top-growth ecom, healthcare, and real-estate operators. I've shipped 100+ production systems and the pipelines I've designed move tens of millions of dollars in transactions every month. Pipelines for AI is where I take that same pattern — same rigor, same boring reliability — and adapt it for businesses that don't have a 50-person data team.

10+ yrsbuilding production data systems
100+production pipelines shipped
$10M+/moin transactions flowing through systems I've built
5×AWS-certified, incl. Solutions Architect Professional

I also publish what I'm building — 3,000+ on the automation tips email list and 3,000+ YouTube subscribers watching the builds in public.

Build for failure. Documentation is part of the deliverable. Real systems teach real lessons. If you'd rather work with someone who's done this in production than someone selling a course about it, that's the bet I'm asking you to make.

11FAQ

The questions buyers email us — before they book.

Short answers to the things people stall on. If yours isn't here, just ask on the call.

Where does our data actually live?

In your own AWS account, in a region you choose. We never copy your data into a vendor cloud, a SaaS dashboard, or our infrastructure. You own the storage, the warehouse, the credentials, and the access controls. We deploy into your account and hand you the keys.

Who owns the code and infrastructure when the engagement ends?

You do. Every line of code, every Terraform/IaC config, every credential, every connector — yours, in a repo you control. We don't keep proprietary "secret sauce" you can't see. If we got hit by a bus tomorrow, your foundation keeps running and any competent data engineer can take it over.

What if you get hit by a bus?

Three things protect you. One: we use standard, widely-supported tooling — not bespoke frameworks only we understand. Two: you own all the source and infra (see above). Three: documentation is part of the deliverable, written for humans, so a new engineer or your in-house team can pick it up cold.

What does data security actually look like?

Encryption in transit and at rest by default. IAM-scoped credentials per source, rotated and logged. No third-party SaaS in the data path — credentials live in your secrets manager, not ours. We can also wire up your existing SSO, VPC peering, or private endpoints if your security team requires them.

Do you handle compliance — HIPAA, SOC 2, GDPR, etc.?

Because everything runs in your AWS account, your existing compliance posture extends to the data foundation. We'll architect to your control set — encryption, access logs, data residency, audit trails — and produce documentation your auditors can read. We've shipped under HIPAA-aligned and SOC 2 environments before. We're not the auditor, but we know how to build for one.

What if our key tool isn't on your supported list?

If it has an API, a database, a webhook, or even an SFTP drop — we can connect to it. If it's a true legacy system with none of those, we'll write a thin wrapper. Custom connectors typically take a week or two and are baked into the engagement.

Can we cancel partway through?

Yes. Standard terms: a 50% deposit kicks off the engagement, the balance is due at handoff. If you cancel after week 2, you keep everything we've shipped to that point — the connectors, the schemas, the docs — and we settle for time spent. If we miss our priority-systems promise (see the offer), the deposit is fully refunded.

How long until we actually see value?

Working data flowing into the foundation typically by end of week 2. First production-grade report or AI-grounding workflow live by end of week 4. Most clients pull at least one manual spreadsheet job out of someone's week before we're even done.

If this fits

Bring your stack. We'll show you the first move.

Book a 30-min call →
12Let's talk

Let's figure out where to start.

Book a 30-minute walkthrough. We'll look at your current stack together, figure out where AI is getting stuck, and map out which apps are worth connecting first. You'll leave with a clear plan — whether or not you work with us.

30 min Video call Working session

A practical walkthrough of the stack you already have.

Bring the apps, sheets, dashboards, and manual handoffs that are slowing things down. We'll map the shortest path to a useful AI interface without turning the whole business into a rebuild.

Available times Loading calendar...
01 Trace the workflow

Where data starts, where it stalls, and who fixes it by hand.

02 Pick the first layer

The fastest connection that makes AI useful instead of noisy.

03 Leave with a plan

Build sequence, rough scope, and what can wait.

Prefer email? hello@gettingautomated.com — tell me what you’re trying to do, I’ll write back honestly whether we’re a fit.