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

Rising Talent

Project details
š¬š¼ššæ šš²š®šŗ š“š²šš š®š»ššš²šæš š¶š» šš²š°š¼š»š±š, š»š¼š šµš¼ššæš. Every answer includes the source document and page number so they can verify and trust it.
šš©šŖš“ ššš š“šŗš“šµš¦š® š¤š°šÆšÆš¦š¤šµš“ šµš° šŗš°š¶š³ š¦š¹šŖš“šµšŖšÆšØ š„š°š¤š“ (šš©š¢š³š¦šš°šŖšÆšµ, šš°šÆš§šš¶š¦šÆš¤š¦, šš°š°šØšš¦ šš³šŖš·š¦), š¶šÆš„š¦š³š“šµš¢šÆš„š“ šÆš¢šµš¶š³š¢š š²š¶š¦š“šµšŖš°šÆš“, š¢šÆš„ š³š¦šµš¶š³šÆš“ š¤šŖšµš¦š„ š¢šÆš“šøš¦š³š“. šš¦šø š„š°š¤š“ š¢š³š¦ šŖšÆš„š¦š¹š¦š„ š¢š¶šµš°š®š¢šµšŖš¤š¢šššŗ.
I built this for NHS England - šš¬,š¬š¬š¬+ documents, šµš®% accuracy, š.š“-šš²š°š¼š»š± response times. Senior staff freed up 5-10 hours/week previously spent answering repeat questions.
š¬š¼ššæ š±š®šš® š»š²šš²šæ š¹š²š®šš²š šš¼ššæ š²š»šš¶šæš¼š»šŗš²š»š. Runs securely in your own cloud.
šš©šŖš“ ššš š“šŗš“šµš¦š® š¤š°šÆšÆš¦š¤šµš“ šµš° šŗš°š¶š³ š¦š¹šŖš“šµšŖšÆšØ š„š°š¤š“ (šš©š¢š³š¦šš°šŖšÆšµ, šš°šÆš§šš¶š¦šÆš¤š¦, šš°š°šØšš¦ šš³šŖš·š¦), š¶šÆš„š¦š³š“šµš¢šÆš„š“ šÆš¢šµš¶š³š¢š š²š¶š¦š“šµšŖš°šÆš“, š¢šÆš„ š³š¦šµš¶š³šÆš“ š¤šŖšµš¦š„ š¢šÆš“šøš¦š³š“. šš¦šø š„š°š¤š“ š¢š³š¦ šŖšÆš„š¦š¹š¦š„ š¢š¶šµš°š®š¢šµšŖš¤š¢šššŗ.
I built this for NHS England - šš¬,š¬š¬š¬+ documents, šµš®% accuracy, š.š“-šš²š°š¼š»š± response times. Senior staff freed up 5-10 hours/week previously spent answering repeat questions.
š¬š¼ššæ š±š®šš® š»š²šš²šæ š¹š²š®šš²š šš¼ššæ š²š»šš¶šæš¼š»šŗš²š»š. Runs securely in your own cloud.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, Conversational AI, Machine Translation, Natural Language Generation, Natural Language Understanding, Sentiment AnalysisAI Development Language
PythonAI Tools
Azure OpenAI, Hugging Face, NVIDIA AI Platform, PyTorchAI Models
BERT, GPT-4, LLaMAWhat's included
| Service Tiers |
Starter
$2,000
|
Standard
$4,500
|
Advanced
$9,000
|
|---|---|---|---|
| Delivery Time | 10 days | 18 days | 30 days |
Number of Revisions | 1 | 3 | 5 |
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)
+$600Frequently asked questions
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SC
Savior C.
Jan 28, 2026
Full-Stack Developer (Vimeo Custom + LiveKit + WebSocket) ā Fix & Stabilize
About Muhammad
Senior AI/ML Engineer | AI Agents & Voice AI | RAG & LLM Pipelines
Lahore, PakistanĀ - 4:48 pm local time
Your support team stops drowning in repetitive calls. Your team finds answers in šš²š°š¼š»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„š²ššš¹šš š šµš®šš² š±š²š¹š¶šš²šæš²š±:
ā¢ š³š¬% drop in manual call volume for a healthcare client (AI voice agent, LiveKit)
⢠Sub-š®-šš²š°š¼š»š± document retrieval across šš¬š+ files (RAG system, NHS England)
ā¢ šµš³% extraction accuracy on structured document processing (OpenAI consultation)
ā¢ šØš¦š š£š®šš²š»š šš¼š¹š±š²šæ in applied AI systems
I am a ššš¹š¹-š¦šš®š°šø + šš/š š šš»š“š¶š»š²š²šæ. You get š¼š»š² š½š²šæšš¼š» who designs the architecture, builds the product, and deploys it. No handoffs between "model people" and "app people."
šš³ šš¼š š®šæš² šµš²šæš² š³š¼šæ š©š¼š¶š°š² šš / šŖš²šÆš„š§š
Your callers get instant responses. Your team handles only the conversations that need a human.
ā¢ šš¶šš²šš¶š, š©š®š½š¶, š§šš¶š¹š¶š¼, šš“š¼šæš®, šš®š»šš
⢠NAT traversal, SFU/MCU, jitter, echo, low-latency tuning, ASR/TTS pipelines
šš³ šš¼š š®šæš² šµš²šæš² š³š¼šæ šš / š š (ššš š, š„šš, šš“š²š»šš)
Your docs become searchable in seconds. Your workflows run themselves. Your AI gives grounded answers with sources, not hallucinations.
ā¢ š„šš with š£š¶š»š²š°š¼š»š² / šššš¦š¦ / šŖš²š®šš¶š®šš² / š½š“šš²š°šš¼šæ - hybrid search, re-ranking, citations
ā¢ šš šš“š²š»šš with šš®š»š“ššµš®š¶š», šš®š»š“ššæš®š½šµ, ššæš²ššš, šš¹š®šŗš®šš»š±š²š
ā¢ šš¹š®šš±š² šš£š, š šš£ šš²šæšš²šæš, šš¼š¼š¹ ššš², šš¹š®šš±š² šš¼š±š² integrations
⢠Models: šš£š§-š°š¼, šš¹š®šš±š², šš²šŗš¶š»š¶, š š¶šššæš®š¹, šš¹š®šŗš®, ššš“š“š¶š»š“šš®š°š²
šš³ šš¼š š®šæš² šµš²šæš² š³š¼šæ š„š¼šÆš¼šš¶š°š šš / š¢š½š²š»šš¹š®š
Your robot learns in simulation and works on real hardware.
ā¢ š¦š¶šŗ-šš¼-šæš²š®š¹ transfer, reinforcement learning, imitation learning
ā¢ ššš®š®š° š¦š¶šŗ, š ššš¼šš¼, š£šššš¹š¹š²š, š„š¢š¦/š„š¢š¦š®, vision-language models for manipulation
šš³ šš¼š š»š²š²š± ššµš² ššµš¼š¹š² š½šæš¼š±šš°š (ššš¹š¹-š¦šš®š°šø)
You get production code, not demo glue:
⢠Frontend: š„š²š®š°š / š”š²š š.š·š (dashboards, admin panels, real-time UIs)
⢠Backend: šš®šššš£š / š”š¼š±š².š·š (REST, WebSockets, auth, payments, integrations)
⢠Infra: šš¼š°šøš²šæ, ššŖš¦/ššš£/ššššæš², CI-friendly deploy
š š "š»š¼-šššæš½šæš¶šš²š" š±š²š¹š¶šš²šæš šššš¹š²
⢠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±š¼š»š²" 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.
