Training Models That Truly Understand Government
General models know the world — but maybe not your business. We train private models on your domain data: models that speak administrative language and understand service processes.
- Continued Pre-training01
- Supervised Fine-Tuning02
- Alignment (RLHF / DPO)03
- Quantization & Distillation04
Bridging General Models and Government Scenarios
Prompt engineering solves part of the problem; professionalism, stability and compliance require training.
Terminology & Standards
Administrative terminology, document standards and processes demand systematic training.
Stability Requirements
Production needs stable, predictable output quality — not demo-day luck.
Data Stays Local
Sensitive data cannot leave the intranet; training must run on private compute and data.
Continuous Evolution
Policies and processes change; models must iterate with business data.
The Complete Chain from Data to Deployment
Six tightly-coupled stages, each with defined deliverables and evaluation gates — no stage advances until quality targets are met.
Four Training Services
Choose a route by goal and budget — from light adaptation to deep training.
Continued Pre-training
Continued Pre-trainingContinued pre-training on large government corpora for deep understanding of administrative language and knowledge.
- Corpus-based learning
- Domain knowledge injection
- Base capability boost
Supervised Fine-Tuning
SFTFine-tuning on high-quality instruction data to master drafting, policy Q&A and service guidance.
- Targeted skills
- Output standardization
- Instruction following
Alignment (RLHF / DPO)
AlignmentPreference optimization from human feedback for safe, rigorous and helpful government-grade outputs.
- Preference data
- Safety alignment
- Refusal & fallback policy
Quantization & Distillation
QuantizationCompress model size while preserving quality; fit different compute budgets with private deployment.
- Quantization
- Distillation
- Inference optimization
Good Models Start with Good Data
We handle the full pipeline under government data security requirements, turning data assets into model capability safely.
Corpus Building
Collection, cleaning and structuring of policies, documents and service guides.
Data Annotation
Professional annotation of instruction and preference data with multi-round QC.
Data Security
Anonymization, access control and compliance review throughout.
Evaluation
Domain eval sets make training outcomes measurable and comparable.
Three Training Routes
Full Fine-Tuning
Full Fine-TuningDeep domain adaptation with the highest quality ceiling.
For core scenarios with ample data and compute
LoRA Efficient Tuning
LoRAParameter-efficient, fast and cost-effective, close to full tuning.
Best value for most scenarios
Adaptation & Prompting
AdaptationLight adaptation with RAG knowledge enhancement — fast results.
For quick validation and knowledge-intensive scenarios
What You Receive
Model Assets
Trained weights, adapters and inference services — owned by you.
Evaluation Report
Benchmark results with baseline comparison analysis.
Technical Docs
Training configs, data specs, deployment guide and reproduction steps.
Training
Enablement on usage, operations and continuous iteration.
Four Steps of a Training Project
Data Preparation
Corpus cleaning, instruction and preference data building, eval sets.
Training
Route selection, hyperparameters, execution and monitoring.
Evaluation & Tuning
Domain evaluation, badcase analysis, iterative optimization.
Deployment & Handover
Private deployment, load testing, docs and training.
Want a Model That Knows Your Business?
A free consultation to assess your data foundation and training feasibility.
Reply within 1 business day