This page describes how LimitlessAI uses AI models, how we handle customer data, and how humans stay accountable for machine output. It is written plainly, so you can hold us to it.
We do not train frontier models, and we will not pretend otherwise. LimitlessAI assembles, configures, and operates AI systems on commercially available foundations. The disclosure, in full:
LimitlessAI uses commercially available AI models and infrastructure from established providers, including OpenAI. Outputs may be reviewed, customized, or configured for specific business use cases.
The model is a component. The system around it — data handling, access boundaries, review structure, audit trail — is what we build, and it is the part we answer for. When AI operates inside your business, accountability for its output sits with us and with the human checkpoints in your workflow. It does not get outsourced to a model vendor.
Numbered so you can quote them back at us — in a scoping call, a security questionnaire, or a dispute. Each one states the rule, then what it means in practice. None of them are aspirations.
We collect and retain only what the workflow requires.
In practiceScoping starts by deleting fields from the plan, not adding them. If an intake workflow needs five fields to do its job, the pipeline sees five fields — not the whole record they came from. Retention is set per workflow at design time, and data with no remaining purpose gets a deletion date.
Access to customer information is least-privilege — for our people and for our services.
In practiceEngineers and services get the narrowest access that lets them do their job, granted by role and revoked when the role ends. Access-control reviews happen during deployment, before production traffic — not after an incident. Nobody at LimitlessAI reads customer data out of curiosity, because nobody can.
Sensitive data stays out of AI pipelines unless the workflow genuinely requires it.
In practiceMost workflows do not need health details, government IDs, or payment credentials to work — so those fields never enter the pipeline. Where a workflow genuinely requires sensitive data, it is flagged at scoping, isolated in handling, and processed deliberately, with the treatment documented in the design you approve.
AI output is reviewed where appropriate — by people, in ways you can inspect.
In practiceUncertain results route to review queues. Confidence thresholds decide what the system may do alone, and you set them. Sampled quality audits check the work it does unsupervised. Autonomy is earned gradually as accuracy is demonstrated — it is never the starting configuration.
AI is used only for the business purposes you authorized.
In practiceThe authorized purposes are written into the engagement. If your data could usefully serve a new purpose, that is a conversation and an amendment — not a quiet configuration change. Scope creep is a breach of this page, and we treat it that way.
Customer data is not used to train public AI models unless you explicitly authorize it.
In practiceYour documents, calls, and records do their job inside your workflow, and nothing else. Any training use requires authorization that is explicit, written, and specific to the data and the model. Silence is a no.
Cite a commitment by its number — "Responsible AI, commitment 04" — in a contract, a security questionnaire, or an email to hello@limitlessai.cloud. We will answer to it.
A commitment that only lives on a webpage is decoration. These surface as checkpoints at three stages of every engagement — where you can watch them happen.
We map every field the workflow touches, then challenge each one to justify its place. Sensitive data is identified here — removed, or given explicit handling rules before anything is built.
How scoping worksLeast-privilege access is configured and reviewed before production, and model accuracy is validated against your real documents — not a benchmark set.
AI operations & securitySystems run monitored on US-based infrastructure we operate, with sampled output reviews and audit logs available whenever you ask for them.
Secure AI hostingThis page governs how we use AI. Four other documents govern the rest — read them together.
What personal information we collect across our services, why, and how long we keep it.
Read the policy PostureOur security and regulatory posture, from infrastructure controls to supported frameworks.
Read the posture ContractThe agreement that governs every engagement and every product we sell.
Read the terms GuaranteeThe 99.999% uptime commitment, with definitions and remedies spelled out.
Read the SLAEvery commitment on this page can be written into your engagement agreement — numbered, specific, and enforceable. Ask, and it goes in.