What we actually do
Most AI projects need some combination of these three things. Pick what you need, skip what you don't.
AI Strategy
Figure out where AI actually makes sense for your business—and where it doesn't. No hype, just honest analysis.
What you get
- Audit of your current operations and data
- Ranked list of AI opportunities by impact vs. effort
- Architecture that fits your existing stack
- Realistic cost and timeline estimates
- The "don't do this" list (often more valuable)
Key outcomes
- Know exactly where to start
- A plan your engineers can actually execute
- Budget numbers you can defend to leadership
- Avoided the "build a chatbot" trap
AI Agents & Automation
Multi-agent systems that handle real workflows—not toys that break when users do something unexpected.
What you get
- Agent architectures that handle edge cases
- LLM apps with proper guardrails and fallbacks
- RAG systems that actually find relevant context
- Integrations with your existing tools
- Monitoring so you know when things go wrong
Key outcomes
- Workflows that run without babysitting
- Hours back for your team each week
- Systems that get better with feedback
- Fewer "the AI said what?" incidents
Data & ML Engineering
Turn messy data into models that work, and models into systems that keep working six months later.
What you get
- Data pipelines that don't break on Mondays
- Models trained on your actual use cases
- Feature stores you can reuse across projects
- Dashboards people actually look at
- Documentation your future self will thank you for
Key outcomes
- Predictions you can trust enough to act on
- One source of truth instead of five spreadsheets
- ML that improves automatically over time
- Data team that ships instead of firefights
How engagements work
Understand
Find the lever
Build small
Scale
We start small, prove it works, then expand. No multi-month discovery phases. No building in isolation. Working software, early and often.
Things you're probably asking
The stuff most consultants make you get on a call to find out.
It depends on scope, but most projects follow this pattern: 2-4 weeks for strategy and scoping, 4-8 weeks for a working proof of concept, then ongoing iteration. We don't do 6-month discovery phases. You'll see working software early.
Not sure which service you need?
That's fine. Most projects touch all three. Let's figure out what makes sense for your situation.
Start a conversation