Two models, two inputs, and no meter on core data

Most teams buy a feed, bolt on a verification service, and add a search tool, then maintain the seams between all three. Morphotech Data runs one dataset underneath all three, so a record that appears in the feed resolves to the same identity in enrichment and in search. You are buying the resolution, not just the rows.

Verification runs continuously rather than in a batch before a sale. Job changes, invalid addresses, and company updates are corrected as they are detected. Every field carries a timestamp and a confidence score, so you can filter on freshness yourself instead of trusting ours.

Every field carries its source, a timestamp, and a confidence score, so a wrong value is something you can point at rather than argue about. Send the record and the field you are questioning, and we trace it to the signal that produced it. The fix is made against the source, not patched on top, and the reason for the change is written onto the field — so the next read of that record shows what changed and when, and the correction shows up in the feeds, in enrichment, and in search rather than only in the place you noticed it. On the money: enrichment is charged per accepted outcome, so an outcome nobody accepted is not billed. Point at the first one and we will fix the rest of that pattern, not just the record you sent.

The rate is a function of two things: the fields you take and the geographies you take. It is not a function of volume. Inside an agreed scope the rate is the rate, so the tenth record costs what the first one cost. Enrichment and verification are charged per outcome — a record fixed — rather than per query, so a search that returns nothing is not billed. There is no per-record meter on the core feed.

Yes. Source, capture timestamp, and a confidence score travel with every field. If a record looks wrong, you can trace it to the signal that produced it and the moment it was last checked, rather than asking us to take it on trust.

Data is delivered to your own storage, so it joins the systems you already run rather than adding another application to operate. Enrichment and search are exposed as APIs, and the same canonical identifiers apply across every layer.

Migration work is quoted separately from the data itself, and scoped with you before anything is committed — because the honest cost depends entirely on what your data looks like. Four things have to happen. Your fields get mapped to ours, so you can see what lands where and what does not. Your records get matched against your own identifiers, so the same company is not loaded twice under two IDs in the system you already run. The two sources run side by side for a while, so you can diff the outcomes and see what actually changes before you depend on it. Then the cutover is a switch, rather than a migration somebody has to babysit. We size all of it against a sample of your real data first rather than a row count, and if part of it is not worth doing for your situation, we will say so before you spend anything on it.

A short conversation about the datasets you run on today, where they break down, and what that costs you. If there is a fit, we scope a concrete slice of your data and prove it on your own records before anything wider is committed.