Intelligent search cut support tickets by 28%
A retrieval-augmented search feature helped users self-serve answers that previously required a support ticket.
AI Consulting
Ship AI features your users actually trust
We help product teams move past AI hype and into shipped, measurable features - copilots, intelligent search, automated workflows, and the data pipelines that support them.
Benefits
Why grounded AI beats a flashy demo
- ✓Shipped, not shelved.
Every engagement targets a feature that reaches production, not a proof of concept that stalls.
- ✓Grounded in your data.
Recommendations are based on your actual users and data quality, not generic best practices.
- ✓Responsible by default.
Guardrails and human-in-the-loop review built in from the first sprint.
- ✓Cost-aware.
Model and infrastructure choices weighed against real inference cost, not just capability.
Our Process
From opportunity audit to shipped feature
- ✓Opportunity audit.
Identify where AI genuinely moves a business metric, and where it doesn't.
- ✓Prototype & evaluate.
Fast prototypes tested against real data before committing to a build.
- ✓Integrate & harden.
Production integration with monitoring, evaluation, and fallback behavior.
- ✓Monitor & iterate.
Ongoing evaluation against quality and cost as usage scales.
Deliverables
What lands in your hands
AI opportunity assessment
A prioritized list of features worth building, and ones to skip.
Working prototype
A tested prototype validated against your real data before full build.
Production integration
Shipped feature with monitoring, evaluation, and fallback behavior.
Responsible AI guardrails
Documented review points and human-in-the-loop checkpoints.
Data pipeline readiness plan
What's needed in your data infrastructure to support the feature long-term.
Cost & performance report
Ongoing visibility into inference cost against quality and usage.
Technology
Tools we build with
Claude
OpenAI
LangChain
Pinecone
Python
AWS Bedrock
Case Studies
AI features that shipped and stuck
Copilot feature adopted by 70% of active users
An in-product assistant helped users complete complex workflows faster, with guardrails reviewed by compliance.
FAQs
AI consulting, answered
No - we can run the engagement end to end, or work alongside an existing data or engineering team if you have one.
We scope data handling and model choice around your compliance requirements upfront, including options that keep sensitive data from leaving your infrastructure.
We evaluate feasibility early with a fast prototype against your real data, specifically so that decision happens in weeks, not after a full build.