FEATURES & CAPABILITIES

Three workspaces. One continuous flow of intelligence.

Data Prep cleans it, Auto Model races it, and the GenAI orchestrator puts it to work — each built for the visual, single-click way k0gn1t operates.

Data Prep

Drag to clean. See it transform.

Slide across a raw, error-riddled dataset and watch it resolve into auto-profiled, color-coded histogram cards — every fix a single visual command.

PROFILED · auto-cleaned0 issues

ageinteger

imputed · 34 avg

incomereal

normalized

regionnominal

3 categories

churnbinomial

label · 30% pos

RAW · customers.csv12 issues

id	age	income	region	churn
1001	34	58,200	EMEA	0
1002	NULL	—	emea	no
1003	29	41000	APAC	0
1004	9999	72,500	NA	1
1005	41	NULL	Apac	yes
1006	37	63,900	EMEA	0

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AUTO MODEL

Race every model family, live.

A competitive scoring matrix that tunes and re-scores in real time. Best metric per column earns a badge — no spreadsheets, no guesswork.

Benchmark · churn-prediction✓ converged

Model family	Accuracy	AUC	F1	Train
Gradient Boosted Trees boosting	94.1%	97.2%	93.8%	4.2s
Random Forest bagging	92.8%	96.1%	92.1%	2.8s
Deep Learning neural	93.3%	95.8%	93.0%	18.6s
Logistic Regression linear	88.7%	91.4%	87.9%	0.6s
Naive Bayes probabilistic	84.2%	88.1%	83.6%	0.3s

GENAI · RAG ORCHESTRATOR

From unstructured PDF to grounded answer.

Map the entire agentic pipeline: segment documents into overlapping chunks, embed to vectors, store securely in Qdrant or Milvus, and stream retrieved context into your LLM of choice.

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PDF Source

unstructured docs

✂️

Segment

overlapping chunks

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Embed

vector coordinates

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Vector DB

Qdrant · Milvus

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LLM

grounded answer

See all 19 operators that power this

Browse the full engine library — searchable, filterable, and ready to drop onto a canvas.