A few representative engagements — the kind of work we take on, and how we approach it. Details are illustrative rather than client case studies; ask us for references from work closer to your industry.
Regional Financial Services Firm
Challenge: Loan-review turnaround was slowing new business, with analysts re-entering the same data across three systems.
Approach: Mapped the review workflow end to end, then built a single intake tool with an AI-assisted first pass on document classification.
Outcome: Analysts spent their time on judgment calls instead of data entry, and average review turnaround dropped meaningfully within the first quarter.
B2B SaaS Platform
Challenge: Customer success couldn’t tell which accounts were at risk until they’d already churned.
Approach: Built a predictive analytics dashboard on top of existing product and support data, surfacing risk signals the team could act on early.
Outcome: The success team moved from reactive save calls to proactive check-ins, with clear before/after visibility into save rates.
Healthcare Logistics Network
Challenge: Manual scheduling across multiple facilities led to recurring bottlenecks during peak demand.
Approach: Ran an operational audit alongside a change-management plan, then layered in an intelligent scheduling assistant to handle routine allocation.
Outcome: Staff kept override control for edge cases, while the routine load shifted onto the system — cutting manual scheduling hours noticeably.
Mid-Market Manufacturer
Challenge: Leadership wanted an AI roadmap but had no reliable inventory of where AI would actually help versus where it was a distraction.
Approach: A focused strategy sprint: audited every candidate use case, scored it against effort and impact, and delivered a prioritized 12-month roadmap.
Outcome: Leadership greenlit two of the four proposed projects with confidence, and shelved the rest without regret.
Working on something similar? Tell us about it and we’ll let you know if it’s a fit.