Lemon ↗
Give the next piece of work to Lemon.
Assistance across your workspace. Included in the platform subscription.
AI Alignment Infrastructure
The platform behind your enterprise’s AI alignment.
Lemon works with your engineers and experts to uncover judgment, engineer benchmarks, and pursue better AI behavior. Expert contributions, coverage, and shared standards give that work a foundation. Trialground supplies managed execution and evaluation evidence.
Lemon · Your AI agent for alignment
Give the work to Lemon. Keep the decisions with your team.
Ask for help with the work in front of you, or direct a specialized capability toward an objective. Lemon prepares findings, proposed changes, and experiments your team can inspect. General assistance and expert elicitation are included in the platform subscription.
Lemon Elicit ↗
Develop expert contributions into usable standards.
Adaptive expert elicitation. Included in the platform subscription.
Lemon Weave ↗
Construct what your coverage calls for.
Cases, worlds, and training material. Metered capacity for the work you authorize.
Lemon Code ↗
Develop a harness through a working conversation.
Interactive harness development. Metered capacity for the work you authorize.
Lemon Goal ↗
Give Lemon the benchmark objective.
Benchmark-driven harness optimization. Metered capacity for the work you authorize.
The shared foundation
Establish what your AI should learn, and where it should hold.
A review can reveal a missing condition. A coverage gap can reveal a question only an expert can settle. The platform connects these findings to standards teams can apply across development.
01
Your experts shape what correct means.
Expert contributions
02Give expert judgment a form teams can apply.
Rubrics and Policies
03Control what your benchmark’s conclusions rest on.
Coverage Engineering
Experts retain authority over judgment. Rubrics express benchmark criteria; policies organize their scope and precedence. Coverage defines the situations and proportions the benchmark should represent.
Trialground
Run agent experiments.
Assess the behavior they reveal.
Runtime manages the execution workload. Evaluation applies your expert criteria to the resulting behavior. Each has a distinct role in developing your agents.
Trialground Runtime
Disposable sandbox computers for agent experimentation.
Run agent harnesses with the tools and worlds they are configured to use. Trialground prepares dependencies, manages execution across benchmark cases, and retains outputs and recorded trajectories so your team can investigate behavior and compare candidates.
Trialground Evaluation
Establish which standards the behavior meets.
Apply expert rubrics to outputs and recorded trajectories. Choose from supported judge models, including Kestel, our specialized binary rubric judge. Compare candidates by policy, rubric, and coverage, with each judgment connected to its criteria and evidence.
Compare Trialground with sandboxes for agents like Daytona, E2B and Modal. See where it fits →
Lemon Goal uses Trialground to test competing harness prototypes. Coverage and shared expert standards give those experiments a basis for comparison, while your engineers decide which changes to integrate.
Teammately models
Our models for evaluation and synthesis.
Meet Kestel and Bower. We fine-tune open-weight models for two demanding tasks: applying expert rubrics and constructing cases across planned coverage. Our objective is fair assessment and useful development material across model families.
Trialground Evaluation
Kestel
Binary rubric evaluation
Assess whether candidate behavior meets each applicable criterion. Kestel is trained for binary rubric judgments, with consistent application across model families as an objective.
Lemon Weave
Bower
Coverage-directed case synthesis
Construct cases around ontology tuples and expert criteria. Bower is trained for coverage-directed synthesis, supporting benchmarks, expert elicitation, and targeted training material.
Start from the work you have
The entry point follows your development question.
Bring existing rubrics, production examples, a benchmark, a harness, or a question for your experts. The first scope can address one unresolved part of the process.
- 01
The expected behavior is still implicit
Begin with your experts. Lemon Elicit prepares contributions that uncover reasoning, exceptions, and preferences, then develops findings into proposed standards for review.
Explore expert contributions ↗ - 02
The benchmark leaves you unsure what has been tested
Begin with representation. Examine the dataset across ontologies, compare it with production usage, and direct Lemon Weave toward missing combinations and consequential conditions.
Explore coverage design ↗ - 03
You have a harness and need to test it
Bring a saved harness and the inputs you want to exercise. Start with execution, then extend the work into benchmark comparisons and rubric evaluation.
Explore the runtime ↗ - 04
A harness needs to be developed or improved
Work with Lemon Code on the implementation. When the benchmark objective is established, Lemon Goal can investigate competing changes through Trialground experiments.
Explore harness development ↗
Within your development stack
Keep production evidence connected to offline development.
Imported interactions help reveal where actual usage diverges from planned benchmark representation. New intents and conditions inform coverage updates, while deliberate coverage preserves rare, consequential situations that recent traffic may not contain.
Build on the tools you already use
Your tracing, evaluation, coding, and training tools can remain part of the process. The initial scope establishes the supported exchange of data and artifacts, together with execution responsibilities.
Go beyond an output rating
Lemon Elicit investigates why an expert made a judgment and which conditions would change it. That reasoning informs reusable criteria, coverage, and subsequent development work.
Keep assessment explicit
Coverage makes the benchmark’s purpose and composition inspectable. Independent assessment helps establish how far an observed gain extends beyond the cases used to develop it.
A concrete starting point
Which part of alignment is holding your team back?
Bring the work you have and the decision you need to make. We can identify the participation, capacity, and evidence needed for a useful first engagement.