Integration
Logistics
API development
Operations data hub for a national transportation organization
A large multi-brand logistics operation was managing shipment data across four separate systems with no unified view. Operational reporting required manual extraction and reconciliation from each platform, consuming analyst time daily and producing results that were always at least 24 hours stale.
We designed a lightweight integration layer that pulled structured data from each source system on a configurable schedule, normalized it to a common schema, and made it available via a single internal API. Branch and regional managers gained access to a live operations dashboard for the first time. Manual reconciliation work was eliminated.
Outcome: Daily analyst reconciliation effort reduced from ~3 hours to zero. Operations dashboards refreshed in near real-time across all brands.
AI automation
Document processing
Workflow
AI-assisted document intake for a relocation services company
A relocation management company was manually processing hundreds of employee move authorization documents per week — extracting policy entitlement data, flagging exceptions, and routing files for approval. The process was slow, error-prone, and dependent on institutional knowledge held by a small team.
We built an AI pipeline that ingested documents in multiple formats, extracted structured fields with high accuracy, applied business rule logic to flag exceptions automatically, and routed clean packages to the appropriate approval queue. A lightweight review interface gave staff visibility into extraction confidence and allowed one-click correction of edge cases.
Outcome: Document intake throughput increased 4x. Exception routing accuracy exceeded manual baseline. Staff time shifted from extraction work to exception review and client communication.
Architecture advisory
Cloud
Technical leadership
Cloud migration strategy for a mid-market services firm
A professional services firm with 300 employees was running critical business applications on aging on-premises infrastructure. Leadership had received proposals from two large systems integrators — both recommending full lift-and-shift migrations at significant cost. They engaged us to evaluate both proposals and provide an independent recommendation before committing.
We reviewed the current environment, assessed application dependencies, and evaluated both vendor proposals against the organization's actual risk tolerance and operational requirements. Our recommendation: a phased approach that migrated high-priority workloads first using managed cloud services, preserved on-premises infrastructure for latency-sensitive systems, and reduced year-one spend by approximately 40% compared to either vendor proposal.
Outcome: Client adopted our recommended approach. Phase 1 completed on schedule. Estimated 3-year TCO reduction of 35% versus the rejected proposals.
Monitoring
Reliability
Operations
Operational monitoring platform for a multi-site service operation
A service business with locations across multiple states had no centralized visibility into the health of their branch-level technology systems. Outages were reported by end users rather than detected proactively, and recovery times were extended because runbooks either didn't exist or were stored in people's heads.
We deployed a lightweight monitoring stack across all locations, defined alert thresholds based on actual business impact, and wrote recovery runbooks for the ten most common failure modes. A central dashboard gave the IT team — two people — real-time visibility into every location. We trained the team on incident response procedure and ran two tabletop exercises.
Outcome: Mean time to detection reduced from "reported by users" to under 3 minutes. Mean time to resolution for common failures reduced by 60%.
Custom development
Internal tooling
Workflow automation
Lead response automation for a service business
A service business was losing bookings to competitors with faster response times. Their process: a lead form submitted, someone noticed it in their email, called back when available. Average response time was measured in hours. The fix didn't require a new CRM — it required wiring the one they had to an automated first-contact flow.
We built a lightweight automation layer that captured new leads in real-time, triggered a personalized acknowledgment within 60 seconds, queued a callback task for the assigned rep, and sent a follow-up sequence if no contact was logged within defined intervals. The entire system ran on infrastructure they already owned.
Outcome: Lead response time from average 4+ hours to under 2 minutes. Booking conversion rate increased measurably in the first 30 days of operation.