biosai-2026
/

BIOS-Insight-v1

@@ -1,517 +1,62 @@
----
-language:
-  - en
-  - my
-license: apache-2.0
-tags:
-  - business-intelligence
-  - sme
-  - myanmar
-  - diagnosis
-  - text-generation
-  - llama
-  - fine-tuned
-  - bios
-  - gold-shop
-  - southeast-asia
-datasets:
-  - BIOS-kernel/myanmar-sme-diagnostics-v1
-base_model: meta-llama/Llama-3.3-70B-Instruct
-pipeline_tag: text-generation
-model_type: causal-lm
-widget:
-  - text: "Diagnose this business: Gold Shop in Yangon, 4.2M MMK monthly revenue, 28% retention rate, team of 3."
-    example_title: "Gold Shop Diagnosis"
-  - text: "What are the top growth opportunities for a Fashion business with 8M MMK revenue in Mandalay?"
-    example_title: "Fashion Growth Opportunities"
----
-<div align="center">
-```
-╔══════════════════════════════════════════════════════════════╗
-║                                                              ║
-║     ██████╗ ██╗ ██████╗ ███████╗                            ║
-║     ██╔══██╗██║██╔═══██╗██╔════╝                            ║
-║     ██████╔╝██║██║   ██║███████╗                            ║
-║     ██╔══██╗██║██║   ██║╚════██║                            ║
-║     ██████╔╝██║╚██████╔╝███████║                            ║
-║     ╚═════╝ ╚═╝ ╚═════╝ ╚══════╝                            ║
-║                                                              ║
-║     Business Idea Operating System                           ║
-║     BIOS-Insight-v1  ·  Kernel: BIOS-kernel-v1              ║
-║                                                              ║
-╚══════════════════════════════════════════════════════════════╝
-```
-**"We don't just analyse businesses. We illuminate them."**
-[![License](https://img.shields.io/badge/License-Apache%202.0-gold.svg)](LICENSE)
-[![Model Version](https://img.shields.io/badge/Version-BIOS--Insight--v1-darkblue.svg)](.)
-[![Language](https://img.shields.io/badge/Language-EN%20%7C%20MY-orange.svg)](.)
-[![Base Model](https://img.shields.io/badge/Base-LLaMA--3.3--70B-purple.svg)](https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct)
-[![Region](https://img.shields.io/badge/Region-Myanmar%20%7C%20SEA-green.svg)](.)
-</div>
----
-# BIOS-Insight-v1 — Business Idea Operating System
-## 🇬🇧 English
-### Model Description
-**BIOS-Insight-v1** is a fine-tuned large language model built on **LLaMA 3.3 70B Instruct**, specifically trained to serve as the intelligence core of the **Business Idea Operating System (BIOS)** — a comprehensive AI agent designed for Myanmar's small and medium enterprises (SMEs), Gold Shops, fashion retailers, F&B operators, and the next generation of Southeast Asian entrepreneurs.
-BIOS is not a chatbot. It is an **Operating System for business ideas** — the same way Windows runs your computer, BIOS runs your business strategy. Every question answered, every weakness surfaced, every opportunity ranked: all orchestrated by a single intelligent kernel.
-This model powers **Module 1: Business Diagnosis Engine**, the foundational layer of the BIOS platform. Feed it 24 structured questions about any business, and it returns a complete, actionable diagnosis in under 60 seconds.
----
-### Architecture & Training
-| Property | Details |
-|----------|---------|
-| **Base Model** | `meta-llama/Llama-3.3-70B-Instruct` |
-| **Fine-tune Method** | QLoRA (4-bit quantisation, rank 64) |
-| **Training Data** | Myanmar SME diagnostics, Gold Shop patterns, SEA business benchmarks |
-| **Context Length** | 8,192 tokens |
-| **Output Format** | Structured JSON — deterministic, parseable |
-| **Languages** | English, Burmese (မြန်မာဘာသာ) |
-| **Quantisation** | GGUF Q4_K_M available for local inference |
----
-### What BIOS Produces
-Given structured business inputs, BIOS-Insight-v1 generates:
-```json
-{
-  "health_score": 47,
-  "health_label": "Fair",
-  "health_dimensions": {
-    "revenue_strength":    40,
-    "customer_retention":  20,
-    "market_position":     60,
-    "technology_adoption": 30,
-    "growth_trajectory":   80
-  },
-  "top_3_weaknesses": [
-    {
-      "rank": 1,
-      "label": "Customer Retention",
-      "your_score": 20,
-      "benchmark": 60,
-      "gap": 40,
-      "severity": "HIGH",
-      "detail": "Only 28% repeat purchase rate — Gold Shop industry average is 60%."
-    }
-  ],
-  "growth_opportunities": [
-    {
-      "rank": 1,
-      "title": "Boost Customer Retention Rate",
-      "expected_impact": "+1,680,000 MMK estimated monthly revenue",
-      "difficulty": "MEDIUM",
-      "timeframe": "2–3 months"
-    }
-  ],
-  "priority_action_items": [
-    {
-      "priority": 1,
-      "action": "Launch a loyalty stamp card and 30-day WhatsApp follow-up sequence.",
-      "composite_score": 82.0
-    }
-  ],
-  "ai_narrative": "Shwe Zin Gold & Jewellery is operating at 47/100 health — a Fair rating that conceals a serious retention gap..."
-}
-```
----
-### Health Score Formula
-The BIOS Health Score is calculated across five equally-weighted dimensions:
-```
-Health Score = (Revenue Strength    × 20%) +
-               (Customer Retention  × 20%) +
-               (Market Position     × 20%) +
-               (Technology Adoption × 20%) +
-               (Growth Trajectory   × 20%)
-Where each dimension is scored 0–100.
-Maximum Score: 100
-```
-| Score Range | Label | Interpretation |
-|------------|-------|---------------|
-| 80 – 100 | 🟢 Excellent | Best-in-class. Scale aggressively. |
-| 65 – 79 | 🔵 Good | Strong foundation. Focus on 1–2 gaps. |
-| 45 – 64 | 🟡 Fair | Visible weaknesses. Targeted fixes needed. |
-| 30 – 44 | 🟠 Below Average | Systemic issues. Restructure required. |
-| 0 – 29 | 🔴 Critical | Immediate intervention. Prioritise survival. |
----
-### Intended Use
-#### ✅ Primary Use Cases
-- **Myanmar Gold Shops & Jewellers** — the lifeblood of Myanmar's retail economy, underserved by digital tools
-- **Fashion & Apparel SMEs** — fast-moving businesses in Yangon, Mandalay, Naypyidaw
-- **F&B Operators** — restaurants, tea shops, catering businesses
-- **Cosmetics & Beauty Brands** — direct-to-consumer Myanmar brands scaling up
-- **Electronics Retailers** — high-value, low-margin businesses needing operational precision
-- **Any Myanmar SME founder** who wants strategic clarity without a consultant's fee
-#### ❌ Out-of-Scope Uses
-- Large corporations (BIOS is tuned for SME scale and context)
-- Non-business tasks (general Q&A, creative writing)
-- Legal or financial advice (BIOS provides business intelligence, not regulated advisory)
----
-### How to Use
-#### With the `transformers` Library
-```python
-from transformers import AutoTokenizer, AutoModelForCausalLM
-import torch
-model_id = "BIOS-kernel/BIOS-Insight-v1"
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model     = AutoModelForCausalLM.from_pretrained(
-    model_id,
-    torch_dtype=torch.bfloat16,
-    device_map="auto",
-)
-system_prompt = """You are BIOS — the Business Idea Operating System.
-You are the elite AI advisor for Myanmar SMEs.
-Always respond in valid JSON with health_score, top_3_weaknesses,
-growth_opportunities, and priority_action_items."""
-user_prompt = """Diagnose this business:
-Business: Shwe Zin Gold & Jewellery | Industry: Gold Shop | Location: Yangon
-Monthly Revenue: 4,200,000 MMK | Retention Rate: 28% | Team: 3 people
-USP: Certified 99.9% pure gold with 10-year buyback guarantee
-Pain Point: No customer follow-up system. Customers don't return.
-12-Month Goal: 12,000,000 MMK
-Marketing Budget: 80,000 MMK/month"""
-messages = [
-    {"role": "system", "content": system_prompt},
-    {"role": "user",   "content": user_prompt},
-]
-input_ids = tokenizer.apply_chat_template(
-    messages,
-    add_generation_prompt=True,
-    return_tensors="pt",
-).to(model.device)
-output = model.generate(
-    input_ids,
-    max_new_tokens=1024,
-    temperature=0.3,
-    do_sample=True,
-    pad_token_id=tokenizer.eos_token_id,
-)
-response = tokenizer.decode(
-    output[0][input_ids.shape[-1]:],
-    skip_special_tokens=True,
-)
-print(response)
-```
-#### With the BIOS Controller (Recommended)
-```python
-from bios_controller import BIOSController, BusinessInputs, ModelBackend
-# Initialise
-controller = BIOSController(
-    backend    = ModelBackend.GROQ,      # or HF_INFERENCE when BIOS-Insight-v1 is live
-    save_to_db = True,                   # persist to NeonDB
-)
-# Fill in the 24 business questions
-inputs = BusinessInputs(
-    business_name              = "Shwe Zin Gold & Jewellery",
-    industry                   = "Gold Shop",
-    location                   = "Yangon",
-    years_in_business          = 7,
-    monthly_revenue            = 4_200_000,
-    team_size                  = 3,
-    target_customer            = "Middle-income families, 30–55, buying gold for investment and festivals",
-    acquisition_channels       = ["Word-of-mouth", "Facebook", "Walk-in"],
-    avg_customer_lifetime_value= 350_000,
-    retention_rate             = 28.0,
-    main_competitors           = "Dagon Gold, KBZ Gems",
-    unique_selling_proposition = "Certified 99.9% gold. Transparent pricing. 10-year buyback guarantee.",
-    sales_channels             = ["Physical Store", "Facebook"],
-    operational_challenge      = "Inventory management",
-    biggest_pain_point         = "No system to follow up with customers after first purchase.",
-    current_technology         = ["Spreadsheets"],
-    marketing_channels         = ["Facebook", "Word-of-mouth"],
-    monthly_marketing_budget   = 80_000,
-    goal_3_month               = 5_500_000,
-    goal_6_month               = 7_000_000,
-    goal_12_month              = 12_000_000,
-    budget_constraint          = "Tight (50-200K)",
-    tech_readiness             = "Somewhat ready",
-    preferred_language         = "English",
-)
-# Run the full diagnosis pipeline
-report = controller.run_diagnosis(inputs)
-# Access structured results
-print(f"Health Score     : {report.health_score}/100  ({report.health_label})")
-print(f"Top Weakness     : {report.top_3_weaknesses[0].label}")
-print(f"Best Opportunity : {report.growth_opportunities[0].title}")
-print(f"\nAI Narrative:\n{report.ai_narrative}")
-# Full JSON output
-print(report.to_json())
-```
-#### With HuggingFace Inference API
-```python
-from huggingface_hub import InferenceClient
-client = InferenceClient(
-    model = "BIOS-kernel/BIOS-Insight-v1",
-    token = "hf_your_token_here",
-)
-response = client.chat_completion(
-    messages=[
-        {"role": "system", "content": "You are BIOS. Respond in JSON."},
-        {"role": "user",   "content": "Diagnose: Gold Shop, 4.2M MMK revenue, 28% retention."},
-    ],
-    max_tokens = 1024,
-    temperature = 0.3,
-)
-print(response.choices[0].message.content)
-```
----
-### Switching Models (Base vs Fine-tuned)
-```python
-controller = BIOSController(backend=ModelBackend.GROQ)
-# Use base LLaMA-3.3-70B (default, available now)
-report_base = controller.run_diagnosis(inputs)
-# Switch to BIOS-Insight-v1 once published on HuggingFace
-controller.switch_to_bios_insight()
-report_bios = controller.run_diagnosis(inputs)
-# Switch back to base
-controller.switch_to_base()
-```
----
-### NeonDB Integration
-```python
-import os
-os.environ["DATABASE_URL"] = "postgresql://user:pass@ep-xxx.neon.tech/neondb?sslmode=require"
-controller = BIOSController(save_to_db=True)
-report     = controller.run_diagnosis(inputs)
-# Retrieve saved report
-saved = controller.get_report(report.session_id)
-# List all diagnoses
-history = controller.list_reports(limit=10)
-```
----
-### Limitations
-- Benchmarks are calibrated for Myanmar market (MMK currency, Yangon/Mandalay/Naypyidaw context)
-- Growth projections are estimates, not guarantees — market conditions vary
-- The model does not access real-time data or the internet
-- Legal and financial decisions should always be reviewed by qualified professionals
----
-### Citation
-```bibtex
-@misc{bios-insight-v1,
-  title        = {BIOS-Insight-v1: Business Idea Operating System for Myanmar SMEs},
-  author       = {BIOS-kernel},
-  year         = {2026},
-  howpublished = {\url{https://huggingface.co/BIOS-kernel/BIOS-Insight-v1}},
-  note         = {Fine-tuned on LLaMA 3.3 70B Instruct for Myanmar business diagnostics}
-}
-```
----
----
-## 🇲🇲 မြန်မာဘာသာ (Burmese)
-### မော်ဒယ်ဖော်ပြချက်
-**BIOS-Insight-v1** သည် **LLaMA 3.3 70B Instruct** ကို အခြေခံ၍ fine-tune ပြုလုပ်ထားသော AI မော်ဒယ်တစ်ခုဖြစ်ပြီး၊ မြန်မာနိုင်ငံ၏ SME (အသေးစားနှင့် အလတ်စားလုပ်ငန်းများ) — ရွှေဆိုင်များ၊ ဖက်ရှင်ဆိုင်များ၊ စားသောက်ဆိုင်များ၊ နှင့် နောင်လာမည့် Southeast Asia ၏ လုပ်ငန်းရှင်များအတွက် **Business Idea Operating System (BIOS)** ၏ AI အဓိကအင်ဂျင်အဖြစ် ဒီဇိုင်းထုတ်ထားသည်။
-BIOS သည် chatbot တစ်ခုမဟုတ်ပါ။ ၎င်းသည် **သင်၏လုပ်ငန်းအကြံဥာဏ်များအတွက် Operating System** တစ်ခုဖြစ်သည် — Windows က သင်၏ကွန်ပျူတာကို run သကဲ့သို့၊ BIOS က သင်၏လုပ်ငန်းဗျူဟာကို run သည်။ မေးထားသောမေးခွန်းတိုင်း၊ ဖော်ထုတ်သော အားနည်းချက်တိုင်း၊ အဆင့်သတ်မှတ်ထားသော အခွင့်အလမ်းတိုင်း — ဆောင်ရွက်မှုအားလုံးကို AI kernel တစ်ခုတည်းဖြင့် လမ်းညွှန်သည်။
----
-### ရည်ရွယ်သောအသုံးပြုနယ်ပယ်
-BIOS-Insight-v1 ကို အောက်ပါလုပ်ငန်းများအတွက် အထူးသင့်တော်သည်:
-**✅ အဓိကအသုံးပြုနယ်ပယ်များ**
-- 🥇 **မြန်မာရွှေဆိုင်များနှင့် လက်ဝတ်ရတနာဆိုင်များ** — မြန်မာ့လက်လီကုန်ခြောက်စီးပွားရေး၏ အသက်ကြောဖြစ်သော ဆိုင်များ
-- 👗 **ဖက်ရှင်နှင့် အဝတ်အထည် SME များ** — ရန်ကုန်၊ မန္တလေး၊ နေပြည်တော်ရှိ ဆိုင်များ
-- 🍜 **F&B လုပ်ငန်းများ** — စားသောက်ဆိုင်၊ လက်ဖက်ရည်ဆိုင်၊ Catering လုပ်ငန်းများ
-- 💄 **လှပရေးနှင့် ကောင်မီတစ်ဆ Brand များ** — မြန်မာ DTC Brand များ
-- 📱 **Electronics ဆိုင်များ** — ကုန်ပစ္စည်းတန်ဖိုးမြင့်သော၊ margin နည်းသောလုပ်ငန်းများ
-- 🏢 **မြန်မာ SME တည်ထောင်သူများ** — consultant ဦးစောင်ကြေးမပေးဘဲ ဗျူဟာကို ရှင်းလင်းစေလိုသူများ
----
-### BIOS ၏ ကျန်းမာရေးရမှတ်ဖော်မြူလာ
-BIOS Health Score ကို ညီမျှသောအချိန်ချိန်ထားသော ကဏ္ဍ ၅ ခုဖြင့် တွက်ချက်သည်:
-```
-Health Score = (ဝင်ငွေခိုင်ခံ့မှု    × ၂၀%) +
-               (ဖောက်သည်ဆက်လက်ဆောင်ရွက်မှု × ၂၀%) +
-               (ဈေးကွက်တွင်နေရာ        × ၂၀%) +
-               (နည်းပညာဆိုင်ရာသုံးစွဲမှု  × ၂၀%) +
-               (တိုးတက်မှုပန်းတိုင်       × ၂၀%)
-အမြင့်ဆုံးရမှတ်: ၁၀၀
-```
-| ရမှတ် | အမှတ်တံဆိပ် | အဓိပ္ပါယ် |
-|------|------------|---------|
-| ၈၀–၁၀၀ | 🟢 ထူးခြားကောင်းမွန်သော | ကဏ္ဍ အကောင်းဆုံး။ တိုးချဲ့ပါ။ |
-| ၆၅–၇၉ | 🔵 ကောင်းမွန်သော | ခိုင်မာသောအခြေခံ။ ကွာဟချက် ၁–၂ ခုကို အာရုံစိုက်ပါ။ |
-| ၄၅–၆၄ | 🟡 ဖြစ်နိုင်သော | မြင်သာသောအားနည်းချက်များ။ ပစ်မှတ်ထားပြင်ဆင်ရန်လိုသည်။ |
-| ၃၀–၄၄ | 🟠 ပျမ်းမျှအောက် | စနစ်ဆိုင်ရာပြဿနာများ။ ပြန်ဖွဲ့စည်းရန်လိုသည်။ |
-| ၀–၂၉ | 🔴 အရေးပေါ် | ချက်ချင်းဝင်ရောက်ကူညီရန်လိုသည်။ |
----
-### မည်သို့အသုံးပြုမည်နည်း (`transformers` နှင့်)
-```python
-from transformers import AutoTokenizer, AutoModelForCausalLM
-import torch
-model_id  = "BIOS-kernel/BIOS-Insight-v1"
-tokenizer = AutoTokenizer.from_pretrained(model_id)
-model     = AutoModelForCausalLM.from_pretrained(
-    model_id,
-    torch_dtype = torch.bfloat16,
-    device_map  = "auto",
-)
-# မြန်မာဘာသာဖြင့် မေးမြန်းနိုင်သည်
-messages = [
-    {
-        "role": "system",
-        "content": (
-            "သင်သည် BIOS ဖြစ်သည် — Business Idea Operating System။ "
-            "မြန်မာ SME များအတွက် elite AI အကြံပေး။ "
-            "JSON ဖော်မတ်ဖြင့် ဖြေပါ။"
-        ),
-    },
-    {
-        "role": "user",
-        "content": (
-            "ဤလုပ်ငန်းကို စစ်ဆေးပါ:\n"
-            "လုပ်ငန်း: ရွှေဇင် ရွှေနှင့် လက်ဝတ်ရတနာ | ကဏ္ဍ: ရွှေဆိုင် | တည်နေရာ: ရန်ကုန်\n"
-            "လစဉ်ဝင်ငွေ: ၄,၂၀၀,၀၀၀ ကျပ် | Retention Rate: ၂၈% | အဖွဲ့ဝင်: ၃ ဦး\n"
-            "အကြီးဆုံးပြဿနာ: ဖောက်သည်များကို ပြန်မလာအောင် ဆက်သွယ်နိုင်သောစနစ��� မရှိ\n"
-            "၁၂ လပန်းတိုင်: ၁၂,၀၀၀,၀၀၀ ကျပ်"
-        ),
-    },
-]
-input_ids = tokenizer.apply_chat_template(
-    messages, add_generation_prompt=True, return_tensors="pt"
-).to(model.device)
-output = model.generate(
-    input_ids, max_new_tokens=1024, temperature=0.3, do_sample=True,
-    pad_token_id=tokenizer.eos_token_id,
-)
-response = tokenizer.decode(output[0][input_ids.shape[-1]:], skip_special_tokens=True)
-print(response)
-```
----
-### BIOS Controller ဖြင့် အသုံးပြုခြင်း
-```python
-from bios_controller import BIOSController, BusinessInputs, ModelBackend
-controller = BIOSController(backend=ModelBackend.GROQ, save_to_db=True)
-inputs = BusinessInputs(
-    business_name           = "ရွှေဇင် ရွှေနှင့် လက်ဝတ်ရတနာ",
-    industry                = "Gold Shop",
-    location                = "ရန်ကုန်",
-    years_in_business       = 7,
-    monthly_revenue         = 4_200_000,
-    team_size               = 3,
-    retention_rate          = 28.0,
-    unique_selling_proposition = "အသိအမှတ်ပြုထားသော ၉၉.၉% ရွှေစစ် — ၁၀ နှစ် buyback အာမခံ",
-    biggest_pain_point      = "ဖောက်သည်များကို ပထမဝယ်ပြီးနောက် ဆက်သွယ်နိုင်သောစနစ် မရှိ",
-    goal_12_month           = 12_000_000,
-    preferred_language      = "မြန်မာဘာသာ",
-    # ... (မေးခွန်း ၂၄ ခုလုံး)
-)
-report = controller.run_diagnosis(inputs)
-print(f"ကျန်းမာရေးရမှတ်: {report.health_score}/၁၀၀ ({report.health_label})")
-print(f"AI အစီရင်ခံချက်:\n{report.ai_narrative}")
-```
----
-### လုံခြုံရေးနှင့် ကန့်သတ်ချက်များ
-- Benchmark များသည် မြန်မာ့ဈေးကွက်အခြေအနေ (MMK ငွေကြေး) အတွက် ချိန်ညှိထားသည်
-- ကြီးထွားမှုခန့်မှန်းချက်များသည် estimate များသာဖြစ်ပြီး အာမခံချက်မပေးနိုင်ပါ
-- ဥပဒေနှင့် ဘဏ္ဍာရေးဆိုင်ရာ ဆုံးဖြတ်ချက်များကို အရည်အချင်းပြည့်ဝသောကျွမ်းကျင်သူများနှင့် ပြန်လည်စစ်ဆေးသင့်သည်
----
-<div align="center">
-**BIOS — Business Idea Operating System**
-*"သင်၏လုပ်ငန်းကို ကျွန်ုပ်တို့ ရိုးရိုးစစ်ဆေးတာမဟုတ်ပါ။ ကျွန်ုပ်တို့ ၎င်းကို လင်းထိန်စေသည်။"*
-*"We don't just analyse businesses. We illuminate them."*
-[![HuggingFace](https://img.shields.io/badge/🤗-BIOS--Insight--v1-yellow)](https://huggingface.co/BIOS-kernel/BIOS-Insight-v1)
-</div>

+---
+language:
+- en
+- my
+license: mit
+tags:
+- business
+- strategy
+- myanmar
+- sme
+- diagnosis
+- startup
+datasets:
+- isaaclk907/bios-ai-train-data
+metrics:
+- health-score
+pipeline_tag: text-generation
+---
+# BIOS-Insight-v1
+**BIOS-Insight-v1** is the intelligence kernel for **BIOS AI**, the first AI Strategy Co-founder specifically designed for Myanmar SMEs. It is optimized to process data from a 24-question diagnostic tool and generate professional, actionable business health reports.
+## Model Description
+The model is fine-tuned to act as an elite business advisor. It takes structured business metrics as input and produces:
+- An overall **Business Health Score (0-100)**.
+- Detailed rationale for 5 key dimensions:
+  1. Revenue Strength
+  2. Customer Retention
+  3. Market Position
+  4. Technology Adoption
+  5. Growth Trajectory
+- Identification of top critical weaknesses.
+- Priority strategic directives and action items.
+- A high-level executive narrative.
+## Myanmar Context Optimization
+Unlike general business models, BIOS-Insight-v1 is calibrated for the Myanmar market:
+- Handles **MMK (Myanmar Kyat)** currency natively.
+- Understands local industry nuances (e.g., Gold Shops, local F&B trends).
+- Tailors growth strategies to Myanmar's digital landscape (Facebook-centric commerce, mobile-first adoption).
+## Usage
+This model is primarily used as the backend for the [BIOS AI Diagnosis Tool](https://github.com/isaaclk91207-oss/BIOSai).
+### Input Format
+The model expects a JSON-like string containing answers to the 24 diagnostic questions, including industry, revenue, team size, and operational challenges.
+### Output Format
+A structured strategic report including scores and professional advice.
+## Training Data
+The model is trained on a synthetic dataset of Myanmar SME personas and professional strategic responses, hosted at [isaaclk907/bios-ai-train-data](https://huggingface.co/datasets/isaaclk907/bios-ai-train-data).
+## Security
+BIOS AI implements "The Fortress" security protocols, ensuring that all data processed by the model is handled with enterprise-grade AES-256 encryption in the integrated platform.
+---
+*Developed by BIOS AI Team for the Myanmar SME Ecosystem.*