You will get Production-Ready Custom LLM Agents with Enterprise RAG Workflows
Rising Talent
Rising Talent
Project details
Architected and deployed custom AI agents and enterprise RAG automation systems using GPT-4, Claude, Gemini, and fine-tuned open-source LLMs to automate complex operational workflows and enterprise knowledge management.
The platform enables natural language interaction across internal documentation, CRM systems, compliance records, sales histories, and operational databases through Retrieval-Augmented Generation (RAG) and AI-driven automation workflows.
Core Capabilities:
• Custom AI agents & workflows
• Enterprise RAG systems
• Internal knowledge search
• Customer support automation
• AI-driven document processing
• Compliance & risk analysis
• CRM/ERP integration
• Multi-LLM orchestration
• Real-time analytics & reporting
• Centralized AI automation workflows
One deployment replaced a 12-person Tier-1 support operation with an AI agent achieving 80% inquiry deflection at 95% accuracy, reducing response time.
Another deployment automated contract review and compliance checking for enterprise operations processing 500+ documents monthly with automated risk scoring.
Designed for enterprise-grade deployment with on-premise architecture and GDPR/SOC2 compliance support.
The platform enables natural language interaction across internal documentation, CRM systems, compliance records, sales histories, and operational databases through Retrieval-Augmented Generation (RAG) and AI-driven automation workflows.
Core Capabilities:
• Custom AI agents & workflows
• Enterprise RAG systems
• Internal knowledge search
• Customer support automation
• AI-driven document processing
• Compliance & risk analysis
• CRM/ERP integration
• Multi-LLM orchestration
• Real-time analytics & reporting
• Centralized AI automation workflows
One deployment replaced a 12-person Tier-1 support operation with an AI agent achieving 80% inquiry deflection at 95% accuracy, reducing response time.
Another deployment automated contract review and compliance checking for enterprise operations processing 500+ documents monthly with automated risk scoring.
Designed for enterprise-grade deployment with on-premise architecture and GDPR/SOC2 compliance support.
AI Development Type
Deep Learning, Recommendation SystemAI Tools
Amazon SageMaker, Azure Machine Learning, Keras, NVIDIA AI Platform, PyTorchAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$1,000
|
Standard
$3,000
|
Advanced
$10,000
|
|---|---|---|---|
| Delivery Time | 10 days | 20 days | 35 days |
Number of Revisions | 1 | 3 | 5 |
AI Model Integration | |||
Detailed Code Comments | - | - | - |
Knowledge Graph | - | - | - |
Model Documentation | |||
Ontology | - | - | - |
Source Code | - | - | - |
Taxonomy | - | - | - |
Optional add-ons
You can add these on the next page.
Additional Revision
+$200Frequently asked questions
About Mirza Ferdous
Enterprise AI Architect | Computer Vision, Voice AI & LLM Systems
Dhaka, Bangladesh - 12:42 am local time
As Founder and CEO of HawkEyes Digital Monitoring, a DUNS-registered and ISO 27001-certified AI company, I architect production AI for British American Tobacco, Unilever, Samsung, and Grameenphone.
The work has expanded outlet coverage by 2.4X, from 500K to 1.2M outlets, with zero headcount added, and cut audit costs by 70% across the board.
Shipped infrastructure, not a pilot deck.
━━━━━━━━━━━━━━━━━━━━━━━━
THE TEAM BEHIND THIS PROFILE
━━━━━━━━━━━━━━━━━━━━━━━━
I joined bKash as employee #18 and helped take it from rollout to Bangladesh's first unicorn. At British American Tobacco I ran sales territories with full P&L responsibility and watched where enterprise operations break. Then I built HawkEyes and a 20+ engineer team to fix those breaks with proprietary AI that holds up in offline-first deployments where shelves are messy, networks drop mid-sync, and merchandiser phones run on old Android versions.
I architect because I lived the problem. I ship because I built the team.
━━━━━━━━━━━━━━━━━━━━━━━━
WHAT WE SOLVE, END-TO-END OR MODULAR
━━━━━━━━━━━━━━━━━━━━━━━━
▸ COMPUTER VISION & IMAGE AI
Retail execution verified in 0.6 seconds. SKU detection across 10,000+ products, share-of-shelf, real-time stockout alerts, planogram and POSM compliance, packaging and defect inspection, and biometric anti-proxy attendance with liveness detection (99% OCR accuracy on ID capture). Powered by M-Lens, our retail execution platform.
▸ VOICE AI & CONVERSATIONAL INTELLIGENCE
Sales conversations audited in 0.8 seconds. Pitch-compliance scoring, intent and objection capture, lead capture, sentiment analysis, real-time next-best-action prompts, and same-day rep coaching. Bundled inside NeuroSales, our DMS engine with PJP optimization, order-to-delivery, credit control, and KPI-linked salary automation.
▸ CUSTOM LLM AGENTS & RAG SYSTEMS
Tier-1 support deflected 80%+. Custom LLM agents with RAG over your institutional knowledge: support automation, multi-turn handling, document processing, intelligent routing, compliance query handling, and escalation workflows.
▸ ACQUISITION AND ACTIVATION AT SCALE
Acquire+ runs eKYC onboarding with NID verification, OCR/ICR, and biometric authentication. Connect+ drives shopper loyalty, D2C e-commerce, and campaign management. PerbuTech powers QR-based AR engagement, virtual games, and consumer profiling. RestoExpress covers 360° restaurant operations: POS, payments, delivery, queues, and reservations.
Every platform is proprietary, customizable, and offline-first. I work hands-on with LangChain, AutoGPT, fine-tuning pipelines, and multi-model orchestration across Claude, GPT-4, Gemini, and open-source LLMs. OutSkill AI Generalist Fellow.
━━━━━━━━━━━━━━━━━━━━━━━━
HOW WE ENGAGE
━━━━━━━━━━━━━━━━━━━━━━━━
Before development starts, we define the scope, pricing, deployment model, IP ownership, source-code access, model usage rights, and handover terms clearly. Client-specific deliverables are protected under the agreed scope, while HawkEyes’ proprietary platform and reusable AI components remain governed by separate licensing terms.
Send a brief with one operational number you cannot move: outlet coverage, audit cost per visit, KYC throughput, support deflection rate, share of shelf, and frontline retention. Include the current cost and the size of the operation it sits inside. The first call maps the bottleneck to measurable AI ROI, sketches a six-week pilot, and tells you whether the math works at your scale. If the business case doesn't justify the investment, I'll tell you before we start.
Steps for completing your project
After purchasing the project, send requirements so Mirza Ferdous can start the project.
Delivery time starts when Mirza Ferdous receives requirements from you.
Mirza Ferdous works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Collection & Workflow Analysis
We review operational workflows, automation objectives, knowledge systems, and integration requirements.
AI Agent & RAG Configuration
The platform is configured based on required AI agents, RAG pipelines, document workflows, and operational automation requirements.