Enterprise data ops & augmentation
Large teams already own a licensed database, a CRM, and a warehouse — and still have coverage holes, decaying records, and manual work nobody has time for. Because B2B data decays about 30% a year, even a well-funded stack degrades between refreshes. Datum augments what you have rather than replacing it: we capture the segments your licensed data misses, chain providers to lift match rates past the 78–84% single-source ceiling, score on your own outcomes, and build agents that fit your governance. Output lands in your systems, with documented provenance on every record.
Enterprise go-to-market doesn't lack tools. It lacks coverage in the corners and the engineering time to keep data clean, current, and scored — and those two shortages reinforce each other, because the team that would fix the coverage gap is the team already behind on everything else.
We work alongside an existing stack rather than proposing a replacement for it: filling the segments your licensed tools miss, keeping records fresh against decay, scoring on your closed-won history, and adding automation where your team does high-volume manual work — inside your security and governance requirements, not around them.
The gaps we're usually called in for
- Coverage gaps persistWhole segments are thin even with enterprise data contracts at $12k–$80k a year.
- Decay outpaces refreshRecords go stale faster than anyone can maintain them, and nobody can say how stale.
- Engineering is the bottleneckData and RevOps work waits behind product priorities, quarter after quarter.
- Provenance is unknownNobody can say where a given field came from or when it was last verified.
- Shadow spreadsheetsTeams maintain private lists because they don't trust the system of record.
How we work inside an existing stack
- 01We integrate with your warehouse and CRM, respecting existing schemas, access controls, and change-management process, and we capture or enrich only where there's a measured gap rather than duplicating what you already license.
- 02We document provenance for every record — which source, which method, which date — so your governance and compliance teams can audit the augmentation the same way they audit a vendor feed.
- 03We fit scoring on your closed-won outcomes and validate it on held-out history, reporting lift by decile rather than an accuracy claim.
- 04Refresh runs on a schedule tuned to how fast each field decays, so the augmentation holds instead of degrading quietly after handoff.
Measure the gap before filling it
The first question in an enterprise engagement isn't what to build, it's how big the problem actually is — and that is usually unmeasured, because measuring it isn't anyone's job. So we start by quantifying coverage against your ICP rather than in the abstract: what share of the accounts you should be reaching are present at all, what share have a verified contact, and how those numbers vary by segment.
Then freshness, which is separately measurable and rarely measured. How old is the average record in each field, when was it last verified, and what proportion has decayed since. Given roughly 30% annual decay concentrated in job changes — 65.8% of contacts change title or function within twelve months — a database refreshed annually is running substantially wrong for most of the year, and the shape of that error matters more than its size.
The output is a map of where the licensed stack is doing its job and where it isn't. That usually reframes the conversation: teams arrive expecting to need a new tool and leave with a narrow, specific augmentation on two or three segments, which is a far cheaper problem.
- Coverage measured against your ICP, by segment
- Freshness measured per field, with age and verification date
- Overlap with existing licensed sources, to avoid paying twice
- A gap map that scopes the build before anything is built
Governance is a design input, not a review gate
In an enterprise the constraint that kills projects is rarely technical. It's that the thing was designed and then presented to security, privacy, and data governance as a finished object requiring approval — at which point either it gets rebuilt or it quietly never ships.
So we treat those requirements as inputs. Data stays in your environment; we work against your accounts and infrastructure rather than exporting to ours. Access follows your existing controls rather than a new set. Every automated write is attributable and reversible. Retention and deletion follow your policies, including for sourced personal data, which carries privacy obligations regardless of how public the source was.
Provenance does a lot of work here. When every field can report its source, method, and date, governance review becomes an audit of a documented process rather than an argument about a black box — and the same record makes it possible to answer a deletion request or a data-subject query without reverse-engineering how something got into the CRM.
Augmenting rather than replacing
We are not trying to displace your licensed database, and we'd be a poor choice for it. Those vendors are genuinely good at the segments they cover, they carry contractual guarantees we don't, and ripping one out is a multi-quarter project with a lot of downside and modest upside.
The useful position is next to it. Chained enrichment sends only the records your primary source missed to secondary providers, so you're paying for the tail rather than re-buying the head. Custom capture targets the specific segments where the licensed data is structurally thin. Scoring runs on your outcomes across both. The result is one resolved, scored account universe where the augmentation is visible as provenance rather than as a separate system nobody trusts.
This is also the reason the work tends to be narrower than expected. Most enterprise stacks are broadly adequate with a minority of segments that are badly wrong in a way that's expensive but localised. Finding that minority precisely is worth more than a broad programme against the whole.
Common questions
Yes, and we design to it rather than seeking approval afterwards. We work inside your environment and access controls rather than exporting data to ours, every automated write is attributable and reversible, and we document provenance so your governance and compliance teams can audit it.
Not if we scope it properly, which is why we measure coverage first. Chained enrichment only sends records your primary source missed to secondary providers, and custom capture targets segments where your licensed data is structurally thin. You pay for the tail, not for the head twice.
Privacy law applies to personal data however public the source was, so sourced records live under the same retention, access, and deletion policies as the rest of your data. Provenance makes that practical: because every field records its source and date, a deletion or subject-access request can actually be answered.
They run in your environment against your accounts, and they're documented so your team can read and operate them. How each build is owned and handed off is scoped per engagement rather than promised as a blanket policy — but nothing depends on our infrastructure staying up.