Integrate with your existing security and oversight processes instead of creating new ones.
Access is enforced through your existing RACF, ACF2, or Top Secret permissions
Patented access technology ensures users can never do more through Geniez than they could in a standard 3270 session
Built-in content moderation for input and output, with adjustable sensitivity and non-disruptive filtering
Works with any LLM your organisation chooses, integrating with your existing AI gateway
No new token-management burden. Usage stays owned and tracked centrally, as it already is today
The Geniez Framework includes configurable content checks on both input and output, letting clients redact sensitive information or block messages entirely based on adjustable sensitivity thresholds. Paired with a Moderation Judge on user input, filtering stays non-disruptive to genuine tasks.
This is the first line of defense, not the only one. Most organisations already run a consolidated AI gateway managing content moderation across all AI access, and Geniez AI has deep experience integrating with these gateways and proxies. We encourage mainframe teams to connect with their internal AI teams first, so implementations build on existing capability rather than duplicating it.
Geniez works with whatever LLM your organisation chooses. Load balancing and access across models is handled at the AI gateway level, where most organisations already manage multiple providers. Routing this through your existing gateway makes switching providers simple, avoids vendor lock-in, and lets teams choose the best model for each task rather than being tied to one.
The Geniez AI Framework doesn't manage token usage or the LLM provider relationship, that stays with the client. Typically this is owned centrally by an AI team, where usage is already tracked. If you're new to token usage, the numbers can look intimidating at first glance, but the reality is far less daunting. Costs vary by model and by input versus output, but a typical 20k-token conversation usually costs just a few cents. Your organisation already has the tools to track and throttle usage by provider, model, or user through your AI gateway; so there's nothing new to build, and nothing extra for mainframe teams to own.
User access enforced through your existing RACF, ACF2, or Top Secret permissions.
Users can never see or do more through Geniez than they can in a standard 3270 session.
Configurable content checks on both what goes in and what comes back.
Choose whether flagged content is redacted or the whole message is blocked.
Tune moderation thresholds to your needs, kept non-disruptive by the Moderation Judge.
Works with your existing AI gateway for moderation, model access, and token tracking.
Use any LLM your organisation chooses, with no vendor lock-in.
Every user authenticates with their RACF ID, and every action is audited.
We don't. The relationship with your LLM provider stays yours, usually managed centrally by your AI team where usage is already tracked. A typical 20k-token conversation usually costs just a few cents, and you can track or throttle usage by provider, model, or user through your existing gateway.
No. Data access is performed locally and controlled by your existing security, and your data is never used to train external models. The connection to mainframe data sources is one-way and secure, with no access from the network side.
Yes. Users authenticate with their RACF ID (ACF2, TopSecret) and all actions are audited, so you retain a complete, attributable record consistent with the controls and processes you already run.
