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AI

AI that ships

We build LLM features, retrieval systems and agents that survive contact with production. Applied where it measurably helps, skipped where it does not.

LLM appsRAG & agentsMLOpsAutomation
vf1 ai --capabilities
genai:llm apps · rag · agents
mlops:deployment · pipelines · monitoring
automation:workflows · back office · qa
guardrails:evals · human in the loop
approach:applied where it pays off
status: models loaded

The shift

AI doesn't replace good engineers. It clears the drudgery, the tests, the docs, the busywork, so your team spends its time on the work that actually matters.

01 · AI services

What we build with AI

From data foundations to deployed models and the guardrails around them. Each engagement is scoped to a business outcome, not a demo.

Data pipelines, ETL and real-time processing built so your AI has clean, reliable data to work with.

ingestion · streaming · quality monitoring · warehousing

Discuss a use case

02 · Industries

Where AI pays off

The domains where applied AI is already earning its keep.

01

Manufacturing

Predictive maintenance and automated quality inspection on the line.

02

Healthcare

Document workflows, triage assistants and analysis tooling for clinical teams.

03

E-commerce

Recommendations, search and support automation that lift conversion.

04

Finance

Fraud detection, risk scoring and compliance document processing.

05

Logistics

Demand forecasting, route optimization and warehouse automation.

06

Education

Adaptive learning platforms and AI tutoring built around the curriculum.

03 · Models

The models we work with

Model-agnostic by design: we pick per task and swap as the field moves.

Claude (Anthropic)
GPT (OpenAI)
Gemini
Llama
Mistral

# Chat assistants, content workflows, document analysis and reasoning.

Closed or open weights, hosted or on your infrastructure. The use case decides.

04 · FAQ

AI questions

What clients ask before we build AI into their product.

Yes. We design for data minimization, keep your data in your own infrastructure or accounts wherever possible, and add guardrails so sensitive data isn't sent to models that shouldn't see it. We're happy to sign an NDA and a data processing agreement.

We treat AI like any other system: evals against your real data, guardrails and fallbacks, a human in the loop where it matters, and monitoring in production. Where a simpler, deterministic solution is more reliable, we use that instead.

We're model-agnostic. We pick per task across Claude, GPT, Gemini, Llama, Mistral and open weights, and swap as the field moves. The use case decides, not a vendor.

No. AI clears the drudgery so your team spends its time on the work that matters. We fold it into delivery where it measurably helps, and skip it where it doesn't.

Yes. We deploy open-weight models and RAG systems on your cloud or on-prem when data residency or cost calls for it, with the same evals, guardrails and monitoring.

Ready to put AI to work?

From LLM features to retrieval and agents, let's find where AI measurably helps your product, then build and ship it.