How much funding has Qalb raised?

Qalb has raised $0.0M in total funding. Their latest funding round was Bootstrapped. Key investors include Muhammad Taimoor Hassan (Self-funded).

Where is Qalb headquartered?

Qalb is headquartered in Auburn, USA. The company has a team of 1-10 people.

Qalb operates in the Natural Language Processing sector. Qalb is a state-of-the-art, large-scale Urdu language model (LLM) designed to provide high-performance natural language processing specifically for the 230 million Urdu speakers worldwide. Delivers superior Urdu linguistic accuracy and cultural nuance versus prior Urdu SOTA (Alif-1.0-Instruct) and base LLaMA-3.1-8B-Instruct by continued pre-training on a curated 1.97B-token Urdu-heavy corpus plus instruction fine-tuning.

When was Qalb founded?

Qalb was founded in 2026. It is based in Auburn, USA.

How much funding has Qalb raised?

Qalb has raised $0.0M in total funding. Key investors include Muhammad Taimoor Hassan (Self-funded).

Who is the CEO of Qalb?

Muhammad Taimoor Hassan is the CEO of Qalb. The company was founded in 2026.

Where is Qalb located?

Qalb is headquartered in Auburn, USA.

What funding stage is Qalb at?

Qalb is currently at the Early Stage stage.

How many employees does Qalb have?

Qalb has approximately 1-10 employees.

Qalb

Category: Natural Language Processing

Qalb is a state-of-the-art, large-scale Urdu language model (LLM) designed to provide high-performance natural language processing specifically for the 230 million Urdu speakers worldwide. Qalb was founded in 2026. The company is led by Muhammad Taimoor Hassan. Based in Auburn, USA. Team size: 1-10. Total funding raised: $0.0M. Latest round: Bootstrapped. Key investors include Muhammad Taimoor Hassan (Self-funded).

Founded: 2026
Headquarters: Auburn, USA
Team size: 1-10
Total funding: $0.0M

Value proposition

Delivers superior Urdu linguistic accuracy and cultural nuance versus prior Urdu SOTA (Alif-1.0-Instruct) and base LLaMA-3.1-8B-Instruct by continued pre-training on a curated 1.97B-token Urdu-heavy corpus plus instruction fine-tuning.

Products and solutions

Qalb-1.0-8B-Instruct (Core LLM, LLaMA-3.1 8B CPT+SFT), Urdu continued-pretraining corpus (1.97B tokens), Ollama / GGUF community distributions, Urdu NLP evaluation across 7 tasks

Unique value

Open Urdu-specialized 8B LLM (LLaMA-3.1 based) trained via continued pre-training on 1.97B tokens; achieves SOTA 90.34 overall on Urdu benchmarks, beating prior Alif-1.0-Instruct (87.1) and base LLaMA-3.1-8B-Instruct (45.7).

Target customer

Software developers, Pakistani tech enterprises, educational institutions, government agencies, and global companies requiring localized Urdu AI integration.

Industries served

Artificial Intelligence, Education & EdTech, Customer Support & Service, Content Creation & Media, Public Sector & Governance

Technology advantage

Urdu-only continued pre-training on diverse high-quality domains (news, literature, government, social media) plus targeted instruction tuning, producing large gains on Urdu tasks while retaining English capability vs English-centric base models.

How they differentiate

Systematic continued pre-training of LLaMA-3.1 8B on a curated 1.97B-token Urdu-heavy corpus plus supervised fine-tuning on Alif Urdu-instruct data, yielding SOTA scores on 6/7 Urdu benchmarks versus prior Alif-1.0-Instruct.

Main competitors

Alif-1.0-Instruct (Traversaal.ai), Meta (LLaMA-3.1 8B-Instruct), Buraq (NUST Research Model)

Key partnerships

Auburn University (Academic Research Support), Hugging Face (Model Distribution), BHT Berlin & BTU Cottbus (Research Collaborations)

Notable customers

Hugging Face Open-Source Community, Academic Researchers in NLP

Major milestones

Released Qalb-1.0-8B-Instruct on Hugging Face in January 2026, Published foundational research paper 'Qalb: Largest State-of-the-Art Urdu Large Language Model for 230M Speakers with Systematic Continued Pre-training' (arXiv:2601.08141, 13 Jan 2026), Developed Urdu-specific continued-pretraining corpus of 1.97 billion tokens, Reached ~4,000 developer downloads and recognition letter from Pakistan's AI & Innovation minister (as of Feb 2026)

Growth metrics

Trained on 1.97B tokens (1.84B Urdu + 140M English); 8B params; overall Urdu benchmark score 90.34 vs Alif-1.0-Instruct 87.1 and LLaMA-3.1-8B-Instruct 45.7; ~4,000 developer downloads as of Feb 2026.

Market positioning

Specialized regional AI infrastructure provider and niche leader in Urdu Natural Language Processing (NLP).

Geographic focus

Pakistan, South Asia, and the global Urdu-speaking diaspora (approx. 230 million people).

Patents and IP

No registered patents disclosed; the project is currently positioned as an open-source contribution with associated academic research (arXiv:2601.08141).

About Muhammad Taimoor Hassan

Muhammad Taimoor Hassan is a serial entrepreneur with ~15 startups built and 13 exits. Microsoft Imagine Cup National Winner and World Finalist (2021). Second-year Master's student in Computer Science and Software Engineering at Auburn University; software engineer/app developer at Auburn Startup Studio (Harbert College of Business).

More Natural Language Processing companies

Official website: https://huggingface.co/enstazao/Qalb-1.0-8B-Instruct