Custom AI, engineered into your systems.
We train models to your domain and engineer the systems around them. Data, deployment, integration. License the platform, or bring us in to ship it end-to-end.
30 minutes. Technical. No pitch.
Working with 4+ design partners across regulated industries.
How We Engage
License the platform, or bring us in to ship it.
Two engagement paths. Pick the one that matches how your team operates.
Platform license
For: Teams with their own ML and data engineers who want the tooling and run the systems themselves.
- Full Ertas platform, self-hosted on-prem or air-gapped
- Named customer success manager and response SLAs
- Training on model training, data prep, retrieval, and deployment
- Roadmap access and direct input on the product
Forward deployment
For: Teams that want the outcome, not the staffing. Our engineers embed, build the system, and hand it to you production-ready.
- We scope, train the models, and engineer the system end-to-end
- Custom-trained models fine-tuned to your domain and data
- Data, retrieval, deployment, and integration all included
- Ownership transferred. Runs inside your infrastructure.
The Challenge
Generic AI doesn't know your domain.
Off-the-shelf models are trained on the public web. Your business runs on contracts, schematics, clinical notes, and workflows that never left your network. That gap is the difference between a demo and a deployment.
Generic models hit quality ceilings
Prompt engineering only goes so far. When accuracy matters on proprietary formats, domain jargon, or private workflows, off-the-shelf models plateau and never improve further.
Data sovereignty is non-negotiable
Regulated teams cannot route sensitive data through third-party inference APIs. HIPAA, GDPR, EU AI Act, and internal policy all point to the same conclusion: sensitive data cannot leave the building.
Costs scale with every call
Per-token API billing turns every feature into a variable cost. At scale, a custom-trained model you run yourself is cheaper, faster, and fully under your control.
From the Field
The same pattern keeps surfacing.
Across industries, team sizes, and geographies: enterprise AI stalls on data, domain specificity, and deployment. Not on models.
The problem is not fine-tuning but cleaning and preparing the diverse data.
AI Lead, Engineering & Construction
700GB+ document archive, 5-person AI team
Making the data cleanup process significantly easier, even if only 80% automated, would be a huge mover.
CTO, On-Device AI Company
Building on-prem AI for manufacturing clients
Clients in enterprise healthcare and legal are more likely to care about on-premises solutions.
Founder, AI Agency
Serving regulated healthcare and legal clients
Compliance
On-premise isn't a preference. It's a requirement.
Regulated industries face compounding compliance obligations. Every major framework points to the same conclusion: sensitive data cannot leave the building.
EU AI Act
Risk-based obligations for high-risk AI systems. Requires technical documentation, data governance, and full data lineage under Article 30.
GDPR
Valid legal basis required for AI training data. Personal data must be minimized, anonymized, or pseudonymized before use in model training.
HIPAA
PHI must be identified and masked before any AI processing. De-identification must meet Safe Harbor or Expert Determination standards.
Data Sovereignty
Regulated industries cannot route data through third-party inference APIs. Data must stay within the organization's own infrastructure throughout the pipeline.
"
Most AI tools process inference over the cloud, making the data essentially public.
Cybersecurity firm, discovery call
Ertas trains, deploys, and runs everything locally. No data leaves the building.
What We Engineer
Four layers, engineered end-to-end.
A custom AI system is more than a model. We engineer the full stack, from data in to deployment out.
Custom-trained models
Fine-tuned foundation models adapted to your domain, your formats, and your workflows. Trained on your data, inside your infrastructure.
Fine-tuning · Distillation · Evaluation · Continuous training
Data infrastructure
Ingest, clean, redact, transform, and label domain data at scale. Every step logged for audit. The training-data foundation most enterprises don't have.
Ingestion · PII redaction · Labeling · Synthesis
Retrieval and context
Retrieval pipelines that give your models live access to your knowledge base. Embeddings, vector stores, and tool-calling endpoints on one canvas.
Embeddings · Vector stores · RAG endpoints · Tool-calling
Deployment and integration
On-prem serving, monitoring, and integration into the systems your team already uses. Runs where your data lives. Works with what you already run.
On-prem serving · Monitoring · API integration · Air-gapped support
Products In Action
Two products. One platform.
Model Studio trains custom models to your domain. Data Pipeline engineers the infrastructure around them. Use one, or both.
Model Studio
Train enterprise-grade models on your own data. Build the fine-tuning graph visually, launch runs on managed GPUs, and export adapters or full GGUF checkpoints into your infrastructure.
Data Pipeline
Engineer the data systems your models depend on. Ingest, redact, transform, and serve. Drag, connect, run. Every node observable. Nothing leaves your network.
PII Redaction
Detect and redact PII/PHI from sensitive documents, score quality, export compliant datasets. Every redaction logged.
30 minutes. Live demo. Scoped to your stack.
Use Cases
Built for industries that can't afford data leaks.
Across regulated sectors, the same pattern repeats: sensitive data, strict compliance, and no SaaS tool that can run behind the firewall.
Construction & Engineering
The Problem
Teams sit on 700GB+ of PDFs, bills of quantities, technical drawings, and inspection reports that cannot be searched or used for AI without manual extraction.
How Ertas Helps
We train estimating and extraction models on your archive, then engineer RAG-powered document search on top. Runs on-prem. Models keep improving as your archive grows.
What Ships
What's yours at the end.
Deliverables, not slideware. Every engagement ships a production system your team owns and can operate.
Custom-trained models
Fine-tuned models adapted to your domain. Evaluated against benchmarks that matter to your business. Ownership transferred to you.
Data pipeline on canvas
A visual pipeline that ingests, cleans, redacts, and transforms your data. Every node observable. Every transformation logged.
RAG and retrieval system
Embeddings, vector store, and a retrieval endpoint your AI agents call via tool-calling. Configured for your knowledge base, deployed on-prem.
Deployment and integration
Serving infrastructure inside your environment. Monitoring, logging, and integration with the systems your team already uses.
Audit trail and compliance reporting
EU AI Act Article 30 ready. HIPAA-aligned logs. Every transformation and export timestamped with operator ID.
Runbooks and enablement
Documentation, training, and operational runbooks so your team can operate, iterate, and extend the system without us.
Forward Deployment
From scoping to production in 90 days.
Forward deployment is how we move fast. Our engineers embed with your team, build the system alongside yours, and hand it off production-ready.
Days 1–30
Scope and foundation
Discovery, data access, compliance review, and baseline evaluation. We map your use case against what's possible and publish a scoped engagement plan.
Days 30–60
Train and iterate
Data pipelines, custom model training, and retrieval system built in parallel. Weekly evaluation checkpoints against your success metrics.
Days 60–90
Deploy and transfer
On-prem deployment, integration with your existing systems, runbooks, and team enablement. By day 90, your team owns and operates the system.
30 minutes. Technical. No pitch.
FAQ
Common questions.
Answers to what enterprise teams typically ask before scheduling a call.
Get Started
Let's scope your system.
Tell us about your domain, your data, and your compliance boundaries. We'll show you what's possible and where Ertas fits. Platform license or forward deployment, we'll recommend the right path.
Prefer to describe your situation first? Email us at hello@ertas.ai