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fernet.consultores

Artificial Intelligence

Generative AI.

Applications built on language models that answer using your own data, with measured quality and controlled costs.

The problem we solve.

A language model answers confidently even when it is wrong. Without controlled access to your data, without evaluation and without cost limits, a generative application can give incorrect answers or expose information it should not.

What’s included.

  • Design of the application and its data sources
  • Information retrieval over your documents
  • Evaluation of answer quality
  • Security and sensitive-data controls
  • Observability of latency, tokens and cost

How we work.

Five phases, always in the same order. Select each one to see what happens in it. In full projects they map onto the stages of our method.

We identify the use case, the data available, the risks and how success will be measured.

We design the solution: models, data, integrations, security controls and traceability.

We build the application on a tightly scoped use case, with retrieval over your sources and sensitive-data controls.

We measure quality with a set of test questions and review cost and latency before extending its use.

We tune the system based on real usage and monitor the system like any other production service.

Technical capabilities.

  • Commercial or open language models
  • Retrieval-augmented generation (RAG)
  • Vector databases
  • Answer evaluation
  • Guardrails
  • OpenTelemetry for GenAI

Use cases.

Internal assistant

Answer questions about your own procedures and documentation.

Summaries

Summarise incidents, reports or case files.

Support

Help support teams with source-based answers.

Benefits for your organisation.

  • Answers grounded in your sources
  • Quality measured, not assumed
  • Controlled cost
  • Sensitive data protected

Deliverables.

  • Application for a tightly scoped use case
  • Evaluation set
  • Architecture documentation
  • Usage, quality and cost dashboards

Frequently asked questions.

Is our data used to train the model?

It depends on the provider and the contract. We review this before choosing, and there are options that run on your own infrastructure.

How do you stop it making up answers?

By limiting answers to your sources, citing them and measuring quality with a set of test questions.

How much does it cost in production?

It depends on volume and the model; we estimate it during the pilot using real usage data.

Shall we talk about Generative AI?

Tell us about your situation. If this service is not what you need, we will tell you; if it is, we will propose a concrete first step.

Request this service