Build AI expertise across your team
The AI expertise gap is holding your team back
You know AI could transform your product. But building AI capability is harder than it looks.
01
No universal AI playbook
If you are waiting for "the universal right way to implement AI", it is not coming. You need to build your own AI playbook. The only way to gather this knowledge is to test with YOUR data.
02
Engineering bottleneck
Every AI question goes to engineering. Product managers and domain experts can't validate ideas independently.
03
Guesswork at scale
You pick GPT-4 because it's popular, not because you've tested it against your actual use cases.
Build AI confidence in 4 steps
Bring Your Real Challenges
Upload test cases from your actual domain—customer queries, documents, data samples. Learn with your data, not generic benchmarks.
Experiment Systematically
Test across 15+ models simultaneously. Compare prompts, parameters, and approaches. Build intuition through hands-on practice.
Get Intelligent Insights
Lovelaice analyzes results and surfaces patterns: which models excel at what, where they fail, and why. The insights a consultant would give you—automatically.
Capture & Share Knowledge
Every experiment builds your team's AI playbook. Document what works, share learnings across teams, onboard new members with accumulated wisdom.
AI expertise for your entire team
Product Managers
Validate AI ideas before involving engineering. Move from 'I think this could work' to 'Here's the data showing it works, at what cost, with what accuracy.'
Engineering Teams
Receive validated configurations with clear requirements. One source of truth for prompts and performance.
Product Leadership
Make AI investment decisions backed by evidence. See clear cost projections and accuracy benchmarks.
Why systematic AI experimentation beats ship-and-hope
Common Approach
Choose GPT-4 because 'it's the best'
Test on 3-10 happy path examples
Write one prompt, then deploy
No cost visibility
PMs waiting on engineering
Learnings stay in scattered docs
Ship and hope it works
With Lovelaice
Test across 15+ LLMs on YOUR data
Test on 50-200 real scenarios including edge cases
Test 2-5 prompt variations, measure performance on each
Predict costs at scale before deployment based on test data
PMs and domain experts run experiments independently
Every experiment documented automatically, builds team playbook
Deploy knowing accuracy, costs, and failure modes
Join teams building AI expertise—not dependency
Lovelaice is more than a platform. It's a new approach to building AI capability.
01
The Methodology
A structured framework for systematic AI development. The same approach top consultants use—now accessible to every team.
02
The Education
Free masterclasses teaching teams to build AI systematically. Hands-on workshops with your actual use cases. Book sessions for your team.
03
The Community
Join product teams building AI expertise together. Share learnings, compare approaches, grow capability collectively.
Your team's AI expertise starts today
The companies winning with AI aren't hiring more consultants—they're building internal expertise. Lovelaice gives your team the tools, methodology, and insights to become AI-capable. Knowledge that stays. Confidence that grows. Results you can prove.