CLIENT CASE STUDIES

Six engagements. Six measurable outcomes. Names are redacted where requested by the client — figures are reported directly from production telemetry.

WAQAR ZAKA

High-Volume NLP Community Agent

Brief. A globally-followed public figure needed a chatbot capable of triaging thousands of daily DMs and community posts without losing nuance.

Build. Multi-intent Python NLP layer with sentiment tracking, custom safety filters, and a fall-through to human moderators for edge cases. Deployed behind an asynchronous worker pool with autoscaling.

Result. 75% reduction in manual moderation time. 24/7 availability with sub-2-second median response time.

  • Python
  • NLP
  • API Integration
  • Redis
Waqar Zaka — Noxyra AI custom NLP chatbot logo

SAAD HASHMANI

Multi-Channel Verification & Marketing Suite

Brief. A growing community needed secure onboarding, automated outreach, and on-site support without scaling headcount.

Build. Three coordinated systems: a Telegram verification bot with abuse heuristics, an embedded website chatbot, and an automated drip marketing engine sharing a single user-profile store.

Result. Thousands of new members onboarded with zero verification incidents. Retention and engagement uplift measured across the first two quarters of deployment.

  • Telegram Verification Bot
  • Website Chatbot
  • Automated Marketing Engine
Saad Hashmani — Noxyra AI verification & marketing bot suite logo

CONFIDENTIAL — PROP TRADING FIRM

XAUUSD Quant EA (Multi-Session)

Brief. A prop firm needed a deployable XAUUSD expert advisor that respected strict drawdown rules across multiple funded accounts.

Build. Session-aware MQL5 EA with walk-forward optimisation against six years of tick data. Risk engine enforces per-account, per-day, and per-position limits with hard kill-switches.

Result. 2.1 Sharpe out-of-sample. 9.4% maximum drawdown. Deployed across 12 prop accounts on a low-latency VPS cluster.

  • MQL5
  • Python Backtest
  • VPS Cluster
  • Risk Engine

CONFIDENTIAL — INTERNATIONAL LAW FIRM

RAG Knowledge Base & Contract Assistant

Brief. Paralegals were burning hours hunting precedent and contract clauses across a 180,000-document archive.

Build. Hybrid retrieval (BM25 + dense vectors) with cross-encoder reranking, citation-grounded LLM responses, and audit logging tied to each user's SSO identity.

Result. 92% reduction in research time on standard contract reviews; verified by sampled internal benchmarks.

  • pgvector + reranker pipeline
  • Citation-grounded answers
  • SSO + full audit trail

CONFIDENTIAL — D2C E-COMMERCE GROUP

WhatsApp Lead-Qualification Engine

Brief. Inbound WhatsApp volume exceeded the sales team's ability to triage. High-intent buyers were waiting hours for a first reply.

Build. Multi-language conversational triage on the WhatsApp Cloud API with intent classification, budget probing, and CRM hand-off inside a single coherent dialogue.

Result. +38% qualified-lead conversion in the first month. 60% reduction in cost-per-lead. Median first-response time dropped to under 30 seconds.

  • WhatsApp Cloud API
  • n8n
  • OpenAI
  • CRM Sync

CONFIDENTIAL — REGIONAL LOGISTICS OPERATOR

Computer-Vision Inventory Counting

Brief. Manual cycle counts across 14 warehouse lanes were slow, error-prone, and routinely missed shrinkage.

Build. YOLOv8 detector with a custom tracker running on NVIDIA Jetson edge devices, syncing real-time SKU counts to the WMS and raising anomaly alerts on unexpected drops.

Result. Daily inventory accuracy rose from 87% to 99.4%. Shrinkage events surfaced within minutes rather than weeks.

  • Edge inference on NVIDIA Jetson
  • Realtime SKU sync to WMS
  • Anomaly + shrinkage alerts

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