Map sources and access
List the approved data, where it lives, who may see it and how current it needs to be.
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03 Connect · Data & AI foundations
Good answers need the right data, the right permissions and the right model. veridive connects approved sources, chooses models on evidence and builds the evaluation that keeps quality visible.
03Connect — Data & AI foundations
Data and AI foundations are the layers under a useful AI system: approved data sources, permission-aware retrieval, the right model for each task, and the evaluation that proves quality. veridive connects these layers to your existing systems and deploys them in your cloud or on-premises, so answers stay grounded, governed and measurable.
03.1 How it runs
List the approved data, where it lives, who may see it and how current it needs to be.
Collect real examples with expert-approved answers and agree the acceptance thresholds.
Build retrieval and pipelines, then compare candidate models on the evaluation set.
Deploy in the agreed environment with quality, cost and access checks running.
≈6–10 weeks
The foundations a first workflow needs are built inside the pilot: retrieval, model choice and evaluation, on approved data.
Monthly
As more workflows come on board, a named team extends the shared foundations, with monthly capacity and service levels agreed together.
03.3 Outcomes
Every answer traces back to an approved source that someone can check.
People see only what they are already allowed to see.
You can switch models when prices or quality change, because the evaluation set shows what you would gain or lose.
The design is model-agnostic, with Anthropic, OpenAI, Google and open-weight models all on the table.
Questions
Usually it is good enough to start, as long as it is reachable. What matters is whether the information a workflow needs lives in approved systems we can access with the right permissions, and whether it is current. We check this early, on your real examples, and if the data is not ready we say so and scope that work first.
The one that performs best on your examples, at a cost you can sustain. We work with Anthropic, OpenAI, Google and open-weight models such as Llama, Mistral and Qwen, and compare candidates on the same evaluation set for quality, cost and speed. Often a smaller model handles most cases and a larger model or a person handles the rest.
Yes. We deploy in your cloud, in a managed environment or on-premises, depending on where your data needs to live. For regulated data that cannot leave your infrastructure, open-weight models can run on your own servers. We map processing locations and access roles up front and align with your KVKK and GDPR requirements.
Tell us which workflow you have in mind. We will reply within one business day with a recommended first step.