OXYGENOXYGEN

For data platforms

Revenue infrastructure for data platform startups

Your buyer is a data team that in half your accounts does not exist yet. Catching the moment it forms is worth more than any list you can buy.

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A data platform gets bought once somebody is finally accountable for data. Until that hire lands the work is spread across three engineers with other jobs and nobody is evaluating anything. After it lands there is a shortlist inside six weeks.

So watch formation rather than size. A first analytics engineer posting, a data team growing while the company is flat, an orchestration tool appearing on the stack. Each lands on the account as a dated fact, and your list is a view over those facts.

Who this is for
Seed to Series A data infrastructure companies: warehouses, pipelines, catalogs, quality, or orchestration. Four to fifty people, founder led revenue, no GTM engineer on staff.
What it looks like today
Databases sell you titles that do not exist yet at your best accounts. A company standing up its first pipeline this month looks identical, on paper, to one that solved the problem two years ago.
What changes
Team formation becomes the filter. Postings name the tools, headcount trends show which function is growing, and detected technology confirms what is already in place before you write anything.

Example searches

Ask for it the way you'd say it

Every search below runs on the same hosted Tables, with the cost previewed before anything is spent.

  • Teams forming right now

    which companies added their first data engineering role in the last two months

    The hire date sits on the account, so you can sort by how recently the function appeared at all.

  • Tools that imply your problem

    show me companies running an orchestration tool and a cloud warehouse together

    Each detected tool is its own column, so a combination becomes a filter and not a review of every account.

  • The person, not the department

    find the head of data or the engineer who owns the pipeline at each company

    Data functions are two or three people at this size, so whoever owns the pipeline is usually the person who will evaluate you, not a gatekeeper passing you on.

Plays

Three motions you can run this week

Each one is a chain of Oxygen primitives — the same hosted objects your workspace already has, composed.

  • Formation-triggered list

    Accounts caught in the weeks while a data function is being built.

    1. Signals
    2. Tables
    3. Records
    1. 1Track data roles and stack changes for your segment into a working table.
    2. 2Promote accounts inside the window and archive the ones that have gone quiet.
    oxygen sourcing plan

  • Watch the stack change

    A shortlist of target accounts whose tooling moved since you last looked.

    1. Tables
    2. Workflows
    3. Records
    1. 1Put the detection column on a scheduled refresh so your target accounts are read again on a cadence you set.
    2. 2Read the cells whose value moved, using the change history to see what the stack was before.
    oxygen tables schedule set

  • Technical proof in the first email

    An opening line about their stack, written from one source of truth.

    1. Knowledge Graph
    2. Tables
    3. Sequences
    1. 1Keep positioning, benchmarks, and common objections in the workspace wiki.
    2. 2Draft a line per row from the detected stack, sample it, then enroll.
    oxygen sequences enroll

Capabilities

What you get

  • Detection that reruns on a schedule

    A scheduled refresh re-reads detected technology across your target accounts, and each cell keeps its change history, so a tool that appeared is something you can see rather than something you hear about six months later.

  • Roles mapped to the stack

    Postings and detected technology sit on the same account, so a list can require both before you spend anything on contact data.

  • Runs you can inspect

    Every column run keeps its provider, cost, and output, so a value in your list can be traced instead of simply trusted.

  • Free workspace, metered spend

    Tables, Records, workflows, and drafts stay unmetered. Enrichment, AI columns, and provider signals draw credits, previewed before each run.

Instead of

The stack this replaces

Native, on one contract and one credit balance — not another tab wired to the last one.

  • Clay
  • Apollo
  • Instantly
  • Attio
  • n8n
  • Airtable

Data sources

What the data actually comes from

Every value lands with its provider and cost recorded on the cell.

  • TheirStack

    Job postings naming the tools a team is standing up, often months before the stack is visible outside.

  • BuiltWith

    Technology detected on a domain, useful here as confirmation rather than as the primary filter.

  • Crustdata

    Headcount by function, which exposes a data team growing inside a company that is otherwise flat.

  • Blitz API

    Finds the engineer or data lead who owns the pipeline, including where no data title exists.

Run these on Oxygen's managed credits, or connect your own provider keys and pay the vendor directly — the same columns, the same runs, the same provenance either way. See every integration.

Limits

Where this stops

  • Internal data stacks are mostly invisible from outside. Detection sees the front of a business, not the warehouse behind it, so treat postings as the stronger evidence and the stack column as a hint.

FAQ

Questions people ask first

Our buyers do not respond to cold email at all.
Many will not, and the answer is fewer accounts with better timing. A company that opened a data role three weeks ago behaves nothing like one picked out of a list of ten thousand.
Can we track when a target account changes its stack?
Yes, though it is a rerun rather than a subscription. You put the detection column on a schedule, the refresh overwrites the cell, and the previous value stays in that cell's history, so the accounts whose stack moved are the ones worth reading. Nothing pushes an alert at you.
Do we need to move our CRM to use this?
No. Records can be the CRM, or it can sync both ways with the one you have. What moves here is sourcing, enrichment, and outbound, where the runs and the spending actually happen.
How does our AI assistant fit into this?
Through the same API the web app calls, exposed as tools. It can build a table and read results back, and any paid step still previews its scope and runs under a ceiling you set.
What happens when a run fails halfway?
Completed rows stay written and the run finalizes with its state visible. A rerun picks up the unfilled rows rather than starting again, so a provider hiccup does not cost you the list.
Is the free tier enough to evaluate this?
It is enough to build the motion end to end. Tables, columns, workflows, and sequence drafts are unmetered, and 10,000 credits cover a first round of enrichment while you judge the data.

Put your GTM motion on one stack

Sign up, get a working workspace with a one-time credit grant, and run the first play end to end without wiring five tools together.

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