The foundation for AI, not another AI solution
Use AI without sending customer data, prompts or IP into public model training. AI Factory runs in your AWS accounts with 60+ guardrails, audit trails and 24/7 operations, so your team can build with AI while the platform boundary is controlled.
What the Factory gives you
Governance by Design
Aligned to the Australian Voluntary AI Safety Standard, ISO 27001, SOC 2 and APRA CPS 234. Controls are managed in Git, with evidence packs exported for audit.
Data Stays Out of Public Models
Where Amazon Bedrock is the right fit, prompts, outputs and tuning data stay out of public model training and away from model providers. We add the AWS controls around it: masking, IAM boundaries, guardrails, logs and evidence.
Proof for Stakeholders
Live dashboards and evidence lakes show regulators, boards and investors that your AI is under control. You get the proof the moment they ask.
Agentic Ops
Secure, autonomous agents that run inside your boundary. Persona patterns, prompts managed in Git, audit trails for every interaction and misuse detection built in. Your developers stop doing things differently across the codebase.
Explore Agentic Ops →What you get
- Persona library Coding, governance, support personas with shared prompts.
- Audit trail Every prompt, response and action logged and reviewable.
- Misuse detection A recommendation agent flags patterns before they reach production.
Guardrails
The managed control framework underneath the Factory. 60+ enforced guardrails across data protection, access, accuracy, cost and regulatory alignment.
See the controls →MLOps
Reproducible pipelines, retraining, drift monitoring and accuracy dashboards for data science teams. Add-on for customers training custom models.
See MLOps →Customer Testimonial
base2Services have been the ones pushing us on better infrastructure for a longer term AI strategy. That strategy, modelling and management is a skill set no one in our business wants to own, and they are a great partner for it.
How we roll it out
Because the security and governance foundation is already built, onboarding can move the first agent or model into production in days, then expand the Factory into ongoing managed operations.
Discovery
One to two days. Scoping workshop, risk and data assessment, first use case selection, pilot scope agreed.
Foundation
Two to three days. Factory deployed in your AWS accounts. Guardrails, evidence pipelines and operator tooling live. Dashboards wired up.
Deployment
Three to four days. First agents or models moved into production with monitoring and audit from day one.
Operate
Ongoing. 24/7 managed operations, guardrail updates, patching and a monthly service review with your team. Fixed monthly fee.
Audited and certified
AWS DevOps Competency
ISO 27001 Certified
AWS SaaS Competency
See what the Factory covers in your environment
Approved pilots include $10,000 in AWS credits. Walk us through your setup and we will show you what the first 30 days look like.
Frequently asked questions
What is base2's AI Factory?
base2's AI Factory is a managed AI operations layer for AWS. It gives teams guardrails, audit trails, MLOps foundations and 24/7 operational support in your AWS accounts.
How does AI Factory keep data out of public models?
AI Factory keeps workloads in your AWS accounts and uses services such as Amazon Bedrock where appropriate, then adds masking, IAM, guardrails, logging and evidence around that boundary.
Where do we draw the line between a bespoke agent and an off-the-shelf chatbot?
If the answer needs your data, your governance requirements or your domain rules, you build inside the Factory. Everything else, use off-the-shelf.
How do we pick the first use case?
We start with a scoping workshop that finds the highest value, lowest risk agent or model. You leave the first session with a prioritised list.
What controls does the Factory give a multi-tenant SaaS for tenant isolation?
Every agent runs under an engineer identity, not a shared account, and the ingestion framework anonymises sensitive fields before they reach non-production.
What does it cost?
Fixed monthly fee for the managed Factory. Pilots include $10,000 in AWS credits.
Can we run the Factory alongside existing DevOps as a Service?
Yes. AI Factory is designed as an add-on to DevOps as a Service and shares the same account access and support team.
How soon can we get started?
Approved pilots move into discovery within days. Because the security and governance foundation is already handled, the first agent or model can go live in days.