Open Infrastructure for Agent Value-Alignment.
ValueAI builds reusable infrastructure for aligning agents: datasets, model artifacts, training recipes, alignment algorithms, and evaluation workflows with clear provenance.
Mission
Open foundations for agents that behave with values in context.
Agent builders should not need to choose between closed alignment tooling and poorly documented public artifacts. ValueAI is building open infrastructure with reuse rights, review evidence, and public-interest stewardship from day one.
Infrastructure standard
Data
Reusable datasets and provenance
Models
Artifacts with evaluation context
Algorithms
Training and alignment methods
Partners
A focused network for open agent infrastructure.
ValueAI works with partners that help make alignment artifacts useful in real agent workflows.
We are especially interested in agent researchers, runtime builders, model trainers, dataset experts, and evaluation teams.
Infrastructure dossier
Release map
Map alignment primitives
Agent test loop
Test against agent behavior
Runtime bridge
Publish integration paths
What ships with a release
Data modules, model artifacts, training or alignment algorithms, evaluation suites, integration notes, provenance, and responsible-use guidance.
Infrastructure pipeline
A reviewable stack for agent value-alignment.
Each release moves through visible gates. The goal is not to make every artifact perfect; it is to make quality, limits, runtime assumptions, and intended use explicit.
01
Map alignment primitives
Define what a release should contain: data modules, model artifacts, training recipes, evaluators, or alignment algorithms.
02
Test against agent behavior
Prototype releases against tool use, planning, delegation, refusal boundaries, and goal-following behavior before claiming utility.
03
Publish integration paths
Ship lineage, usage guidance, evaluation context, known constraints, and integration notes for Splendor Kernel and open agent stacks.
Roadmap
Transparent enough to evaluate, restrained enough to trust.
We are sharing direction without flooding the site with low-signal status tags. The work is sequenced around artifacts that make open agent value-alignment credible in practice.
Phase 01
Phase 02
Phase 03
FAQ
Clear answers for early collaborators.
What is shipping first?
We are preparing the first release standard and pilot artifacts now. Releases may include data, models, training or alignment algorithms, and evaluation workflows once review notes are ready.
Who is ValueAI for?
Researchers, nonprofits, and AI teams building agents that need reusable alignment infrastructure with licensing clarity and enough context to evaluate fitness for use.
How does Splendor Kernel fit?
Splendor Kernel is the open runtime integration path. ValueAI artifacts are shaped so they can be tested in real agent workflows rather than remaining static research assets.
Collaborate
Help shape the first release standard.
Share an agent infrastructure need, review perspective, runtime integration, or partnership idea. We will keep the conversation grounded in what is real, reviewable, and useful.