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ABExperiment by DataKnobs

Experiment across experiences, models, prompts, and intelligent decision Knobs.

ABExperiment is the optimization layer for DataKnobs. Test KreateWebsites experiences, KreateBots behavior, Data Product logic, EKIP configurations, and high-impact Knobs against measurable business, quality, risk, and cost outcomes.

Explore ABExperiment See the DataKnobs platform
DataKnobs product architecture

ABExperiment connects creation, governance, evaluation, and optimization.

It provides a common experimentation layer for digital experiences, assistants, agents, Data Products, model configurations, and decision Knobs.

KREATECreate websites, assistants, agents, datasets, and Data Products.
ABExperimentDefine hypotheses, variants, exposure rules, and success metrics.
EKIPEvaluate quality, safety, drift, evidence, and behavior.
KontrolsEnforce policy, approvals, compliance, and release conditions.
KnobsPromote and tune high-impact variables using experiment evidence.
ABExperiment capabilities

One experimentation and optimization layer across the DataKnobs platform.

EXPERIMENT

KreateWebsites experiments

Compare page layouts, headlines, calls to action, forms, navigation, local experiences, and personalized journeys.

EXPERIMENT

KreateBots experiments

Evaluate prompts, retrieval strategies, system instructions, tools, agent plans, and response formats.

EXPERIMENT

Model and infrastructure experiments

Compare approved models and infrastructure on quality, latency, safety, cost, task completion, and business value.

EXPERIMENT

Knob experiments

Adjust feature weights, thresholds, ranking logic, autonomy, safety, retrieval, and recommendation Knobs.

EXPERIMENT

Multi-dimensional outcome measurement

Track conversion, engagement, completion, quality, compliance, operational efficiency, cost, and downstream impact.

EXPERIMENT

EKIP closed-loop learning

Use experiment evidence to promote better configurations into Data Products, KreateWebsites, KreateBots, and EKIP.

Experiment operating model

Designed for governed experimentation across the full DataKnobs lifecycle.

Every hypothesis, variant, exposure, outcome, and promotion decision is connected to the same Data Product, lineage, policy, and feedback loop.

Hypothesis01
Variants02
Exposure03
Outcomes04
Learning05
Experimentation Knobs

Test the variables that materially change outcomes.

ABExperiment helps teams isolate, compare, and optimize the highest-impact controls across AI, data, and digital experiences.

Experience knobLayout, messaging, CTA, journey, personalization, and channel configuration.
Conversion
Prompt knobInstructions, examples, format, tone, reasoning depth, and tool guidance.
Response quality
Retrieval knobSource selection, authority, freshness, top-k, chunking, and evidence.
Grounding
Model knobProvider, model, temperature, route, latency, caching, and infrastructure.
Quality / cost
Scoring knobFeature weights, thresholds, formulas, segmentation, and confidence.
Decision accuracy
Recommendation knobRanking, eligibility, diversity, next-best action, and user preference.
Relevance
Safety knobPolicy thresholds, escalation, approval, autonomy, and prohibited actions.
Risk control
Outcome knobPrimary metric, guardrail metrics, holdout, duration, and decision criteria.
Evidence
Business outcomes

Turn experimentation into measurable product and business improvement.

Deploy ABExperiment independently or combine it with KreateWebsites, KreateBots, Data Products, EKIP, Knobs, and Kontrols.

✓
Improve conversion, engagement, completion, and customer guidance
✓
Reduce model and infrastructure cost while protecting quality and safety
✓
Validate prompts, models, Knobs, and experience changes before production rollout
✓
Optimize prompts, models, retrieval, ranking, scoring, and recommendation logic
✓
Create a measurable Data → Signals → Data Products → Consumption → Feedback → Knobs flywheel

Make ABExperiment the optimization layer of your DataKnobs platform.

Start with one experience, assistant, model, or Data Product decision. Define the outcome, test controlled variants, and promote the evidence-backed winner.

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