Lineage you can trace
Every field back to the system that produced it, with the transformation in version control. If you cannot trace it you cannot defend it.
AI
The data platform the pilot needed and never had.
Almost every stalled AI project we are called into has the same cause: the data exists, but nobody can say where it came from, when it was last correct, or who is allowed to see it.
Softrear builds the data foundations AI depends on: ingestion and lineage, quality checks with alerting, a modelled warehouse, vector storage where retrieval requires it, and access control that survives an audit.
How it works
Quality checks with alerts
Freshness, volume, null rate and referential integrity tested on every load, alerting when they drift — not discovered in a model’s output three months later.
A modelled warehouse
Facts and dimensions your analysts recognise, documented and tested, rather than a lake full of raw exports nobody trusts.
Vectors where they earn it
Embeddings and a vector index for the retrieval that genuinely needs semantic search. A great deal of what gets embedded should have been a filtered SQL query.
Access control at the row
Who may see which records, enforced in the platform rather than in each application — because AI surfaces make quiet access failures loud.
Also in AI
Assistants and agents
An assistant in production needs three things a demo does not: a bounded set of actions, a record of what it did, and a way to measure whether it is getting better or worse.
AI readiness assessment
The cheapest way to find out whether an AI project is worth doing is to spend two weeks finding out, with people who will tell you if the answer is no.
Tell us what’s stuck.
A senior engineer reads every one of these. If we’re not the right fit we’ll say so, and point you at someone who is.
Start the conversation
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