Adaptive Small Language Models for Privacy-Focused Businesses
Bring the power of AI to your private business, without sacrificing security, efficiency, or control.
Enterprise use of LLMs is risky
General‑purpose chat AIs are powerful, but they often send information outside your network, change without notice, and make it hard to prove what happened.
- Law firm: A paralegal uses ChatGPT to summarize a box of scans. It’s fast, but causes headaches when opposing counsel asks how the summaries were produced.
- Bank: A loan officer pastes income statements into Claude to “speed up” analysis. It works—until inconsistencies are found and no one can explain how the analysis was done.
- Insurance: An adjuster sends call transcripts to Google Gemini to auto‑draft notes. Leadership starts asking why outputs keep changing.
LLM risk include:
Confidentiality violations, PII/PHI data breaches, Inconsistent outputs, Weak audit trails, Unpredictable costs, Cross‑border data transfer risk, Third‑party retention of prompts
SLMs offer a Secure, Private, and Task Specific Alternative
Run small, task-specific models inside your walls for the everyday work. If something truly unusual shows up, fall back to a larger model deliberately. Your data stays private, results are more consistent, and costs are predictable.
Private AI for Enterprise
SLMander helps privacy-focused businesses harness the intelligence of AI safely, through custom Small Language Models (SLMs) designed for privacy, specialization, and full ownership.
The future of AI is smaller, smarter, and secure.
Why Small Language Models?
Privacy
Your private data stays safe and secure inside your private network.Efficiency
Lower compute, faster deployment, reduced costs and energy use.Control
Create hyper-specialized usage cases that excel at key tasks.Why NVIDIA Is Betting on SLMs
“Most agentic AI use cases don't need LLMs — they need smaller, specialized, efficient, and locally deployable SLMs.”NVIDIA Research — “Small Language Models Are the Future of Agentic AI” (Belcak et al., 2025) • Read the paper
Core Opportunity
- Replace generalized API calls with on-prem SLMs tuned for specific, repeatable workflows.
- Lower latency, higher determinism, and stronger tool-use reliability.
- Own your intelligence: weights, logs, governance — inside your firewall.
How SLMander Delivers
| Opportunity | Description | Value Proposition |
|---|---|---|
| SLM Migration Audits | Assess where LLM use can be replaced by local SLMs. | “Cut 80% of your AI inference costs without sacrificing performance.” |
| VaultSLM Buildouts | Design secure, on-prem systems with task-specific SLMs. | “Run AI inside your own firewall.” |
| SLM Fine-tuning Service | Offer LoRA / QLoRA fine-tunes using collected internal data. | “Transform usage data into proprietary expertise.” |
| Compliance & Trust Layer | Build frameworks for regulated industries. | “Private, auditable, compliant AI intelligence.” |
Consulting & Custom Builds
- SLM Readiness Audits — data, compliance, and integration pathways.
- Custom SLM Development — train, deploy, and host private models.
- Maintenance & Optimization — continuous tuning, retraining, and security support.
Who We Serve
The Future of AI, Made Compliant
SLMander bridges the gap between innovation and regulation. We help privacy-first organizations step confidently into the AI era with technology that adapts to your rules, and custom built models that live within your walls.
Book Your Free Strategy Call
Tell us a bit about your organization and goals. We'll follow up with scheduling options.
What to Expect
- Discovery Call (Free) — objectives, constraints, compliance scope.
- Readiness Audit — data sources, infrastructure, integration plan.
- Pilot Build — deploy VaultSLM™ in an isolated environment.
- Scale & Maintain — tuning, monitoring, and governance.