AI Consulting
A clear view of where AI creates real value in your business, and the roadmap to get there. The work is led by the engineer who designs and ships the production AI workflows — practical implementation, not slideware.
The Approach
The engagement starts with your business problem. Structured workshops identify the highest-impact use case for AI in your operations, followed by a proof of concept that demonstrates real value before you commit to a full rollout.
The Outcome
A clear AI roadmap with prioritized use cases, validated by a working prototype. You know exactly what to build, what it costs, and what ROI to expect before writing a single line of production code.
You're overwhelmed by AI options
New models, frameworks, and tools launch every week. Your team is interested, but the choices blur together. You need someone who builds with these tools daily to compare them against your workflow and pick what is worth testing.
You're afraid of investing in the wrong approach
AI projects fail when teams choose technology before defining the business problem. The wrong model, architecture, or use case can waste months of budget. You need a roadmap before you start building.
You are spending on tools your team does not use
Your team signed up for three AI tools last quarter. Two are sitting idle because they were never mapped to an actual workflow. Strategy before tools saves you months of wasted licenses.
What's Included
- 01
AI readiness assessment
- 02
Use case identification and prioritization
- 03
Model and tool selection guidance
- 04
Implementation roadmap and architecture
- 05
Cost-benefit analysis and ROI projection
- 06
Team training and knowledge transfer
Deliverables
An AI readiness assessment that names what is feasible now and what is not
A use case catalog ranked by payoff and implementation effort
A technical architecture recommendation matched to your existing stack
An implementation roadmap with milestones your team can execute against
An executive summary you can present internally without translation
Frequently Asked Questions
The engagement assesses your current systems, identifies high-impact AI use cases, evaluates the right models and tools, and delivers an implementation roadmap. Depending on scope, this includes workshops with your team and a final presentation for stakeholders.
Yes. Many clients move directly into the AI and Automation service after consulting. The roadmap is designed to be actionable, whether webvise builds it or your team does.
Sebastian Kehle leads the work directly, with hands-on experience building LLM integrations, automation pipelines, and AI-assisted internal tools for production use. The focus is practical implementation: scoped workflows, clear architecture, and systems your team can operate.
Starting with the technology instead of the problem. Teams pick a model or a framework, then look for something to do with it. The projects that work start with a specific, measurable pain point and work backward to the simplest solution that addresses it.
Built with Compliance in Mind
Every AI solution follows practices aligned with ISO 42001 for responsible AI management and ISO 27001 for information security.