دراسات

Teams were exporting telemetry and KPI data into ad-hoc spreadsheets. Answers were slow, inconsistent, and security requirements ruled out sending data to external LLM APIs.

A lightweight chat UI backed by a query service that routes questions to the appropriate data source, executes safe queries, and returns summaries with computed results, all within private infrastructure.

Model selection was inconsistent and slow. Ad-hoc tests used different prompts, lacked versioning, and made it hard to compare cost, latency, and quality across providers.

A benchmarking utility with a web UI that includes a versioned dataset registry, a parallel sweep runner, a scoring module, a YAML config editor, CSV/JSON exports, a report table, and a log inspector.

Teams were stuck exporting conversation data manually, cleaning it by hand, and stitching reports across tools. Metrics were inconsistent, insights were delayed, and it was hard to ask questions across all conversations in one place.

A distributed analytics service with connector sync, normalization, retention policies, report generation, and a chat-style query layer; plus an internal dev utility to trigger syncs, inspect logs, and preview ingested data.

Campaign budgets were being drained by bot traffic, proxy farms, and repeated clicks. Teams had no unified way to filter traffic, track suspicious visits, or enforce rules per campaign.

A fraud screening API with an admin dashboard for campaigns, filters, and traffic logs, plus configurable link protection and alternate redirects.

Traders were manually checking multiple exchanges and missing short-lived spreads. Data was inconsistent across sources, and raw price differences ignored fees, causing noisy alerts.

A Rails-based backend with a price aggregation layer, alert rules engine, and a lightweight dashboard for managing watchlists and reviewing alerts.

Shared desks and meeting rooms were being double-booked, and employees lacked a clear view of availability across dates and locations. Existing tools were too heavy for quick, on-the-spot bookings.

A web app with day-based navigation, a real-time floor plan, quick booking actions, and a personal reservations view, plus authentication for employees only.

Limited-quantity drops were being drained by resellers using bulk orders and address clustering. Manual review was slow, rules were inconsistent across teams, and abuse signals lived in separate systems.

A backend service with real-time scoring, address clustering, bulk-order detection, automated limits, and a review workflow, plus APIs and reporting for reseller activity.

Calendars only check free time, not whether a meeting is useful. Professionals were accepting agenda-less meetings, 60-minute defaults, and oversized calls that destroyed focus and created hidden workload costs.

A lightweight extension that adds a “meeting quality panel” to invites. Users see overload warnings, estimated cost of the meeting, and buttons to propose shorter, async, or delegated options.

Operational teams lacked real-time visibility into streaming data and anomaly signals. Existing pipelines were batch-oriented, slow to detect issues, and difficult to scale during traffic spikes.

A distributed real-time processing platform with stream ingestion, rule-based enrichment, anomaly detection, and an operations dashboard with live metrics and alerts.

Operations relied on spreadsheets and disconnected systems, leading to stock mismatches, delayed schedules, and poor visibility into production performance.

A warehouse management web app that unifies inventory, production scheduling, order processing, and operational reporting with role-based dashboards.