The kind of work we take on.
AIC is a young consultancy, and these are representative engagement types described in depth rather than a public case study archive with named clients just yet. As we complete projects where the client agrees to be named publicly, we will publish full write ups here in their place.
Multi Tenant Analytics Platform
The challenge
A growing product team needed to turn an internal reporting tool into a sellable, multi tenant SaaS product, without the months of rework that usually comes with retrofitting tenant isolation onto a system that was never designed for it.
Our approach
We designed a data model with tenant isolation built in from the schema level up, rather than filtering by tenant at the application layer, which reduced the risk of a query bug ever leaking one customer's data into another's view. Usage based billing was integrated early so pricing could be tested against real usage patterns before general availability.
The outcome
The platform launched with self serve onboarding, tenant level usage dashboards, and a billing system that scales with account growth without manual intervention from the team.
Internal Operations Agent
The challenge
A support team was spending hours each day triaging incoming requests manually, most of which followed predictable patterns that did not require human judgment to route correctly.
Our approach
We built a tool calling agent that reads incoming requests, checks them against internal documentation and prior resolutions, and either drafts a response for review or escalates automatically when confidence is low. The agent was scoped to read only access initially, with write permissions added only after several weeks of monitored accuracy.
The outcome
Response drafting time dropped significantly, and the team now spends its attention on the requests that genuinely need human judgment instead of the routine majority that do not.
Manual Reporting Pipeline Replacement
The challenge
A weekly revenue report was assembled by hand from three separate internal systems, a process prone to copy paste errors and dependent entirely on one person's availability each week.
Our approach
We built an automated pipeline that pulls from each source system on a schedule, reconciles the data, and generates the same report format the team was already used to reading, so adoption required no retraining. Monitoring was added so failures are caught and alerted on before the report is due, not after someone notices it missing.
The outcome
The report now generates itself every week with no manual intervention, and the underlying pipeline has since been extended to feed two additional internal dashboards.
Public Facing Product Marketing Site
The challenge
A product team needed a marketing site that could be updated by non engineers without going through a deployment cycle for every content change, while still loading fast and ranking well in search.
Our approach
We built the site on Next.js with a lightweight, custom content layer connected to a headless CMS, so the marketing team could publish new pages and update copy independently. Performance budgets were set early and enforced through automated checks in the deployment pipeline.
The outcome
The site consistently scores in the high nineties on Lighthouse performance and SEO audits, and the marketing team has shipped dozens of content updates since launch without engineering involvement.
Field Service Scheduling System
The challenge
A service business was coordinating technician schedules across spreadsheets and phone calls, leading to double bookings and technicians arriving without the correct job information.
Our approach
We built a scheduling system centered on real time availability, with a technician facing mobile view showing job details, customer history, and required parts. Conflict detection was built directly into the scheduling logic rather than relying on dispatchers to catch overlaps manually.
The outcome
Double bookings were effectively eliminated, and technicians now arrive with complete job context, reducing the number of return visits caused by missing information.
Document Intelligence for Contract Review
The challenge
A legal operations team needed to extract key terms from a high volume of incoming vendor contracts, a task that was consuming significant paralegal time each week.
Our approach
We built a document processing pipeline that extracts key clauses, flags terms that deviate from the organization's standard playbook, and surfaces a structured summary for human review. The system was explicitly designed to assist review rather than replace it, since contract review carries real legal risk if automated end to end.
The outcome
Initial review time per contract dropped substantially, with the paralegal team now focusing their attention on flagged deviations instead of reading every clause from scratch.