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About ReliablyME Inc.
ReliablyME Inc. is the company behind ReliablyME and its next generation, ReliablyWE. Our focus is the gap between an intention and dependable follow-through: what people agreed to, what happened next and whether the result met the agreement.
ReliablyME: the existing product
ReliablyME supports commitments and follow-through for people and teams, with evidence to help review what happened. It is the foundation for the next generation—not simply another name for the company.
ReliablyWE: the next generation
ReliablyWE is being developed to extend that foundation across people, organizations and AI agents. Ari, its assistant, is designed to help the parties clarify agreements, navigate blockers and bring evidence to the people authorized to review and accept the result.
The important change is a connected collaboration experience: a request becomes an agreement; work proceeds within the right authority; and a delivered result remains distinct from acceptance. This matters when useful AI output still needs people to coordinate, make decisions and stand behind an outcome.
ReliablyWE's intended experience is illustrated in the fictional story. It does not establish that all depicted capabilities are deployed or available for an engagement.
Our approach
- Start with a real outcome. Understand the workflow and the people who depend on it before choosing a technical solution.
- Make agreements explicit. A request and an accepted commitment are not the same thing.
- Use evidence to help people. Make the basis for a result understandable, rather than reducing people to an unexplained score.
- Keep people in charge. Consequential decisions need the appropriate human authority.
- Be clear about what is available. Separate current capabilities, prototypes and planned work for the specific engagement.
Our purpose: Make trust tangible.
We want increasingly capable AI to strengthen human agency, not obscure who agreed to act or who can decide.
Boundaries we design to:
- No surveillance: focus on the commitment and what followed, not everything a person does.
- Proportional evidence: use only the evidence the reviewer needs for that commitment.
- Support, not punishment: use understandable coaching signals, not rankings, ratings or disciplinary scores.
- Human authority: AI can assist and act only within authority delegated by the appropriate people or institutions.
- No hidden influence: no hidden behavioral scores, dark patterns or inferences presented as decisions. Identify AI recommendations as suggestions.
- Authority that can be withdrawn: make delegated authority legitimate, limited, traceable to its source and revocable. A click alone does not establish meaningful control.
Founder
Alex Todd is the founder and CEO of ReliablyME Inc. His work centers on how organizations turn intentions into commitments and follow-through.
Explore the idea
Watch the fictional ReliablyWE story to see the intended experience, or bring a workflow you would like to discuss.
ReliablyWE is in development. The story is illustrative; it is not a customer deployment or a promise of availability for every depicted feature.