CUSTOM SLM MODELS
Custom small language models
for private enterprise AI.
Get the power of private AI without the cost and privacy trade-offs of large cloud models. We fine-tune custom small language models on your business data and deploy them in your environment, alongside AI agent development, recruitment AI, website design, ad channel management, and AI content systems.
1B-7B parameter models that understand your domain better than GPT-4, running on your hardware, at a fraction of the cost.
Small models,
trained on your data.
A custom small language model is a compact AI model fine-tuned on your proprietary business data, so it understands your domain vocabulary, workflows and use cases without relying on a generic cloud LLM.
We fine-tune the model on approved business data and deploy it in your environment: on-premise servers, Docker containers, Kubernetes clusters or controlled cloud infrastructure.
Purpose-built private SLM models that outperform generic AI on your tasks.
01 /What we build
Custom small language model development
for private AI.
Purpose-built private SLM models that outperform generic AI on your tasks.
Domain-Specific SLM Training
Compact models fine-tuned on your proprietary data, with your terminology in the weights.
- Fine-tune custom small language models on your proprietary data - product catalogs, support tickets, internal docs
- Domain vocabulary and terminology baked into the model weights for private enterprise AI
- Outperforms generic LLMs on your specific use cases at a fraction of the cost
Private On-Premise AI Deployment
Models that run inside your network on infrastructure you already control.
- Run private SLM models on your own infrastructure - no data leaves your network
- GPU and CPU deployment options with optimized inference
- Docker containers and Kubernetes-ready for easy scaling
Cost Efficient AI Inference
Small models on modest hardware with fixed, predictable costs.
- Small models (1B-7B parameters) that run on modest hardware
- 10-100x cheaper than API calls to large cloud models
- Predictable fixed costs instead of per-token pricing
Fast Edge AI Performance
Low-latency inference for real-time and high-throughput workloads.
- Sub-100ms response times for real-time applications
- Quantized models for edge deployment on consumer GPUs
- Batch processing pipelines for high-throughput workloads
02 /Comparison
Custom SLM vs Cloud LLM API
for enterprise AI.
How a private small language model compares with calling a large cloud model over an API.
| Custom SLM | Cloud LLM API | |
|---|---|---|
| Cost per query | $0.0001 | $0.01-0.10 |
| Latency | <100ms | 500ms-5s |
| Data privacy | On-premise | Sent to third party |
| Domain accuracy | Trained on your data | Generic |
| Uptime control | You own it | Vendor dependent |
03 /Use cases
Custom small language model
use cases.
Where teams put private SLM models to work.
Product descriptions
Product description generation trained on your catalog style.
Private knowledge Q&A
Private enterprise knowledge Q&A without sending data to third parties.
Document processing
Automated data extraction and document classification with custom SLMs.
Regulated industries
Compliance-safe on-premise AI for regulated industries.
04 /Good to know
Good questions.
Straight answers.
Something else on your mind?
support@zeonsolutions.ai
What is a custom small language model?
A custom small language model is a compact AI model fine-tuned on proprietary business data so it understands domain vocabulary, workflows, and use cases without relying on a generic cloud LLM.
Can custom SLM models run on-premise?
Yes. ZEON Solutions deploys custom SLM models in private environments, including on-premise servers, Docker containers, Kubernetes clusters, and controlled cloud infrastructure.
How do small language models reduce AI costs?
Small language models typically use fewer parameters and can run on modest hardware, reducing per-query costs and replacing unpredictable token-based pricing with controlled infrastructure costs.
What business data can be used to train a private SLM?
Private SLM training can use approved internal documents, product catalogs, support tickets, policies, knowledge bases, CRM notes, and workflow examples to improve domain accuracy.
How are custom small language models used with AI agents?
Custom small language models can power private AI agents for support, document processing, content generation, data extraction, and internal knowledge workflows without exposing sensitive data to public AI APIs.
Next /Start a conversation
Ready to train your own
private AI model?
Tell us about your data and use case and we will scope a custom SLM for you. Need the agents that run on it? See our AI agent development.