Custom Small Language Models (SLMs)
Turn your internal documents, playbooks, and institutional knowledge into a private AI that answers with your voice. Our SLMs are firm‑owned, secure, and tuned to your workflows helping teams move faster with confidence.
What Is an SLM?
A Small Language Model focuses on depth over breadth. Unlike a public, general chatbot, it’s a domain‑specific model trained on your organization’s knowledge base and curated industry resources, aligned to your tone, policies, and compliance needs.
Key Benefits
- Faster answers: Retrieve precedents, policies, and prior work in seconds.
- Consistent outputs: Standardize language and reasoning across all deliverables.
- Scalable knowledge: Preserve expertise and speed up onboarding for new staff.
- Compliance‑ready: Guardrails, citations, and role‑based access for verifiable answers.
Applications
- Professional Services: Retrieve work product, align drafting, and accelerate client intake.
- Public Sector & Education: Policy retrieval, permitting FAQs, multilingual guidance, and onboarding.
- Architecture, Engineering & Construction: Code references, spec templates, RFP libraries, design review support.
- Healthcare & Nonprofits: Compliance checklists, grant writing, and program documentation.
Our Process
- Discovery: Map use cases, governance, and success metrics.
- Secure Ingestion: Process PDFs, docs, emails, wikis, and databases with access tagging.
- Model Tuning: Align to tone, templates, and decision logic; integrate citations and guardrails.
- Pilot & Rollout: Launch, measure, iterate, and train staff for adoption.
Security & Compliance
- Deployed to your secure environment (cloud or on‑prem) with encryption at rest/in transit.
- Role‑based permissions and optional prompt/response logging with redaction.
- Citations and provenance tracking back to approved documents and policies.
FAQs
How is this different from ChatGPT?
Public models are general and shared. Your SLM is private, trained on your data, tuned to your voice, and governed by your controls.
Do we keep ownership?
Yes, your environment, your data, your model.
What about accuracy?
We require citations, apply guardrails, and tune to your templates and decision logic.