Most AI projects fail on the data, not the model
The model is the easy part now. What stops an AI project is data that is dirty, undocumented, full of unclassified personal information, and impossible to explain after the fact.
How DataLens approaches it
Clean before you embed
Nulls, duplicates and mixed types are as damaging to a retrieval index as to a report, and much harder to spot afterwards.
PII found before it spreads
Personal data is flagged at ingest, so the decision about whether it may reach a model is made once, early, rather than discovered later.
Documents as a first-class source
Document collections are stored whole and retrieved from, which is what grounds generation in your own material.
Prompts are versioned artefacts
A prompt lives in the library, bound to a flow and sealed into a release — not pasted into a node where nobody can find the version that produced last month’s output.
Every call is accounted for
Cost, tokens, latency, failures and cache hits per step, with estimates against actuals, because an AI pipeline without cost observability becomes an unexplained invoice.
Golden datasets catch regressions
A known input with a known expected output, kept with the release, so a prompt change that degrades quality is caught before promotion.
The stages this leans on
The rest of the lifecycle is there when you need it.
Questions
Does DataLens train models on my data?
No. AI steps call the provider whose credentials you supplied, using your key and your account.
How do I stop personal data reaching a model?
PII columns are flagged at ingest and policies can restrict what may be done with them, so the restriction is enforced by the platform rather than remembered by a person.
How do I know whether a prompt change made things worse?
Golden datasets. A known input with a known good output is evaluated as part of the release, so a regression fails the promotion instead of reaching production.
See it on your own data
DataLens is in private beta. Bring a file, a database or an API and work through the whole lifecycle in one sitting.
Request beta access