You will get RAG System: Sub-Second Answers From 10K+ Documents

Muhammad A.Status: Offline
Muhammad A. Muhammad A.
5.0
Rising Talent

Let a pro handle the details

Buy Generative AI services from Muhammad, priced and ready to go.
Muhammad A.Status: Offline
Muhammad A. Muhammad A.
5.0
Rising Talent

Let a pro handle the details

Buy Generative AI services from Muhammad, priced and ready to go.

Project details

š—¬š—¼š˜‚š—æ š˜š—²š—®š—ŗ š—“š—²š˜š˜€ š—®š—»š˜€š˜„š—²š—æš˜€ š—¶š—» š˜€š—²š—°š—¼š—»š—±š˜€, š—»š—¼š˜ š—µš—¼š˜‚š—æš˜€. Every answer includes the source document and page number so they can verify and trust it.

š˜›š˜©š˜Ŗš˜“ š˜™š˜ˆš˜Ž š˜“š˜ŗš˜“š˜µš˜¦š˜® š˜¤š˜°š˜Æš˜Æš˜¦š˜¤š˜µš˜“ š˜µš˜° š˜ŗš˜°š˜¶š˜³ š˜¦š˜¹š˜Ŗš˜“š˜µš˜Ŗš˜Æš˜Ø š˜„š˜°š˜¤š˜“ (š˜šš˜©š˜¢š˜³š˜¦š˜—š˜°š˜Ŗš˜Æš˜µ, š˜Šš˜°š˜Æš˜§š˜­š˜¶š˜¦š˜Æš˜¤š˜¦, š˜Žš˜°š˜°š˜Øš˜­š˜¦ š˜‹š˜³š˜Ŗš˜·š˜¦), š˜¶š˜Æš˜„š˜¦š˜³š˜“š˜µš˜¢š˜Æš˜„š˜“ š˜Æš˜¢š˜µš˜¶š˜³š˜¢š˜­ š˜²š˜¶š˜¦š˜“š˜µš˜Ŗš˜°š˜Æš˜“, š˜¢š˜Æš˜„ š˜³š˜¦š˜µš˜¶š˜³š˜Æš˜“ š˜¤š˜Ŗš˜µš˜¦š˜„ š˜¢š˜Æš˜“š˜øš˜¦š˜³š˜“. š˜•š˜¦š˜ø š˜„š˜°š˜¤š˜“ š˜¢š˜³š˜¦ š˜Ŗš˜Æš˜„š˜¦š˜¹š˜¦š˜„ š˜¢š˜¶š˜µš˜°š˜®š˜¢š˜µš˜Ŗš˜¤š˜¢š˜­š˜­š˜ŗ.

I built this for NHS England - šŸ­šŸ¬,šŸ¬šŸ¬šŸ¬+ documents, šŸµšŸ®% accuracy, šŸ­.šŸ“-š˜€š—²š—°š—¼š—»š—± response times. Senior staff freed up 5-10 hours/week previously spent answering repeat questions.

š—¬š—¼š˜‚š—æ š—±š—®š˜š—® š—»š—²š˜ƒš—²š—æ š—¹š—²š—®š˜ƒš—²š˜€ š˜†š—¼š˜‚š—æ š—²š—»š˜ƒš—¶š—æš—¼š—»š—ŗš—²š—»š˜. Runs securely in your own cloud.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer Model
AI Applications
AI Chatbot, Conversational AI, Machine Translation, Natural Language Generation, Natural Language Understanding, Sentiment Analysis
AI Development Language
Python
AI Tools
Azure OpenAI, Hugging Face, NVIDIA AI Platform, PyTorch
AI Models
BERT, GPT-4, LLaMA
What's included
Service Tiers Starter
$2,000
Standard
$4,500
Advanced
$9,000
Delivery Time 10 days 18 days 30 days
Number of Revisions
135
AI Model Integration
-
Batch Normalization
-
-
-
Database Integration
Detailed Code Comments
-
-
Image Upscaling
-
-
-
MLOps
-
-
Model Deployment
Model Documentation
Model Monitoring
-
Model Testing & Optimization
Model Tuning
-
Natural Language Processing
NLP Tokenization
Pre-Training
-
-
-
Prompt Engineering
Setup File
-
Source Code
Optional add-ons You can add these on the next page.
Additional Data Source Integration (+ 2 Days)
+$400
Slack + Teams Integration (+ 3 Days)
+$500
Role-Based Access Controls (+ 4 Days)
+$600

Frequently asked questions

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SC

Savior C.
5.00
Jan 28, 2026
Full-Stack Developer (Vimeo Custom + LiveKit + WebSocket) – Fix & Stabilize
Muhammad A.Status: Offline

About Muhammad

Muhammad A.Status: Offline
Senior AI/ML Engineer | AI Agents & Voice AI | RAG & LLM Pipelines
5.0 Ā (1 review)
Lahore, PakistanĀ - 4:48 pm local time
š—Ŗš—µš—®š˜ š—°š—µš—®š—»š—“š—²š˜€ š˜„š—µš—²š—» š˜†š—¼š˜‚ š—µš—¶š—æš—² š—ŗš—²:

Your support team stops drowning in repetitive calls. Your team finds answers in š˜€š—²š—°š—¼š—»š—±š˜€ instead of digging through documents for hours. Your manual workflows run on autopilot while your people focus on work that actually needs a human brain.

š—„š—²š˜€š˜‚š—¹š˜š˜€ š—œ š—µš—®š˜ƒš—² š—±š—²š—¹š—¶š˜ƒš—²š—æš—²š—±:
• šŸ³šŸ¬% drop in manual call volume for a healthcare client (AI voice agent, LiveKit)
• Sub-šŸ®-š˜€š—²š—°š—¼š—»š—± document retrieval across šŸ­šŸ¬š—ž+ files (RAG system, NHS England)
• šŸµšŸ³% extraction accuracy on structured document processing (OpenAI consultation)
• š—Øš—¦š—” š—£š—®š˜š—²š—»š˜ š—›š—¼š—¹š—±š—²š—æ in applied AI systems

I am a š—™š˜‚š—¹š—¹-š—¦š˜š—®š—°š—ø + š—”š—œ/š— š—Ÿ š—˜š—»š—“š—¶š—»š—²š—²š—æ. You get š—¼š—»š—² š—½š—²š—æš˜€š—¼š—» who designs the architecture, builds the product, and deploys it. No handoffs between "model people" and "app people."

š—œš—³ š˜†š—¼š˜‚ š—®š—æš—² š—µš—²š—æš—² š—³š—¼š—æ š—©š—¼š—¶š—°š—² š—”š—œ / š—Ŗš—²š—Æš—„š—§š—–

Your callers get instant responses. Your team handles only the conversations that need a human.
• š—Ÿš—¶š˜ƒš—²š—žš—¶š˜, š—©š—®š—½š—¶, š—§š˜„š—¶š—¹š—¶š—¼, š—”š—“š—¼š—æš—®, š—š—®š—»š˜‚š˜€
• NAT traversal, SFU/MCU, jitter, echo, low-latency tuning, ASR/TTS pipelines

š—œš—³ š˜†š—¼š˜‚ š—®š—æš—² š—µš—²š—æš—² š—³š—¼š—æ š—”š—œ / š— š—Ÿ (š—Ÿš—Ÿš— š˜€, š—„š—”š—š, š—”š—“š—²š—»š˜š˜€)

Your docs become searchable in seconds. Your workflows run themselves. Your AI gives grounded answers with sources, not hallucinations.
• š—„š—”š—š with š—£š—¶š—»š—²š—°š—¼š—»š—² / š—™š—”š—œš—¦š—¦ / š—Ŗš—²š—®š˜ƒš—¶š—®š˜š—² / š—½š—“š˜ƒš—²š—°š˜š—¼š—æ - hybrid search, re-ranking, citations
• š—”š—œ š—”š—“š—²š—»š˜š˜€ with š—Ÿš—®š—»š—“š—–š—µš—®š—¶š—», š—Ÿš—®š—»š—“š—šš—æš—®š—½š—µ, š—–š—æš—²š˜„š—”š—œ, š—Ÿš—¹š—®š—ŗš—®š—œš—»š—±š—²š˜…
• š—–š—¹š—®š˜‚š—±š—² š—”š—£š—œ, š— š—–š—£ š˜€š—²š—æš˜ƒš—²š—æš˜€, š˜š—¼š—¼š—¹ š˜‚š˜€š—², š—–š—¹š—®š˜‚š—±š—² š—–š—¼š—±š—² integrations
• Models: š—šš—£š—§-šŸ°š—¼, š—–š—¹š—®š˜‚š—±š—², š—šš—²š—ŗš—¶š—»š—¶, š— š—¶š˜€š˜š—æš—®š—¹, š—Ÿš—¹š—®š—ŗš—®, š—›š˜‚š—“š—“š—¶š—»š—“š—™š—®š—°š—²

š—œš—³ š˜†š—¼š˜‚ š—®š—æš—² š—µš—²š—æš—² š—³š—¼š—æ š—„š—¼š—Æš—¼š˜š—¶š—°š˜€ š—”š—œ / š—¢š—½š—²š—»š—–š—¹š—®š˜„

Your robot learns in simulation and works on real hardware.
• š—¦š—¶š—ŗ-š˜š—¼-š—æš—²š—®š—¹ transfer, reinforcement learning, imitation learning
• š—œš˜€š—®š—®š—° š—¦š—¶š—ŗ, š— š˜‚š—š—¼š—–š—¼, š—£š˜†š—•š˜‚š—¹š—¹š—²š˜, š—„š—¢š—¦/š—„š—¢š—¦šŸ®, vision-language models for manipulation

š—œš—³ š˜†š—¼š˜‚ š—»š—²š—²š—± š˜š—µš—² š˜„š—µš—¼š—¹š—² š—½š—æš—¼š—±š˜‚š—°š˜ (š—™š˜‚š—¹š—¹-š—¦š˜š—®š—°š—ø)

You get production code, not demo glue:
• Frontend: š—„š—²š—®š—°š˜ / š—”š—²š˜…š˜.š—·š˜€ (dashboards, admin panels, real-time UIs)
• Backend: š—™š—®š˜€š˜š—”š—£š—œ / š—”š—¼š—±š—².š—·š˜€ (REST, WebSockets, auth, payments, integrations)
• Infra: š——š—¼š—°š—øš—²š—æ, š—”š—Ŗš—¦/š—šš—–š—£/š—”š˜‡š˜‚š—æš—², CI-friendly deploy

š— š˜† "š—»š—¼-š˜€š˜‚š—æš—½š—æš—¶š˜€š—²š˜€" š—±š—²š—¹š—¶š˜ƒš—²š—æš˜† š˜€š˜š˜†š—¹š—²
• Clear milestones (what ships in week 1 vs week 3)
• A testable slice early so you see progress fast
• Clean handoff: documented setup + deploy notes

Tell me what "š—±š—¼š—»š—²" looks like for your project and I will respond with an execution plan.

Steps for completing your project

After purchasing the project, send requirements so Muhammad can start the project.

Delivery time starts when Muhammad receives requirements from you.

Muhammad works on your project following the steps below.

Revisions may occur after the delivery date.

Document audit and retrieval design

I analyze your document types, test chunking strategies on sample docs, and design the retrieval architecture (vector search, hybrid search, or both).

Ingestion pipeline and search build

Build the document processing pipeline, configure embeddings, set up the vector database, implement hybrid retrieval with re-ranking, and add source citations.

Review the work, release payment, and leave feedback to Muhammad.