REPOGEO REPORT · LITE

uptrain-ai/uptrain

Default branch main · commit a31cc14e · scanned 5/20/2026, 3:21:41 AM

GitHub: 2,346 stars · 203 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

40 /100

Critical

Category recall

0 / 2

Not recommended in any query

Rule findings

2 pass · 0 warn · 0 fail

Objective metadata checks

AI knows your name

3 / 3

Direct prompts that named your repo

HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface uptrain-ai/uptrain, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION

hightopics#1

Add specific LLM evaluation and monitoring topics

Why:

CURRENT

autoevaluation, evaluation, experimentation, hallucination-detection, jailbreak-detection, llm-eval, llm-prompting, llm-test, llmops, machine-learning, monitoring, openai-evals, prompt-engineering, root-cause-analysis

COPY-PASTE FIX

autoevaluation, evaluation, experimentation, hallucination-detection, jailbreak-detection, llm-eval, llm-prompting, llm-test, llmops, machine-learning, monitoring, openai-evals, prompt-engineering, root-cause-analysis, llm-monitoring, ai-observability, llm-guardrails, llm-evaluation-platform

highreadme#2

Move core value proposition to the very top of the README

Why:

COPY-PASTE FIX

Place the following text as the absolute first content in the README, before any badges, links, or videos: 'UpTrain is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured evaluations (covering language, code, embedding use cases), perform root cause analysis on failure cases and give insights on how to resolve them.'

mediumreadme#3

Add a 'Why UpTrain?' or 'Comparison' section

Why:

COPY-PASTE FIX

Add a new section titled 'Why UpTrain?' or 'UpTrain vs. Alternatives' that explicitly states: 'UpTrain's core differentiator is its comprehensive, open-source platform for continuous evaluation, monitoring, and guardrailing of LLM applications in production. Unlike tools that often focus on specific aspects (e.g., just evaluation or just monitoring), UpTrain provides a unified solution from development to production.'

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall

0 / 2

0% of queries surface uptrain-ai/uptrain

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

DeepEval

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

DeepEval · recommended 2×
LangChain · recommended 2×
Weights & Biases (W&B) · recommended 1×
Arize AI · recommended 1×
MLflow · recommended 1×

CATEGORY QUERY
How can I automatically evaluate and improve my Generative AI application's performance?
you: not recommended
AI recommended (in order):
1. Weights & Biases (W&B)
2. Arize AI
3. MLflow
4. DeepEval
5. LangChain
6. Giskard
7. Humanloop
AI recommended 7 alternatives but never named uptrain-ai/uptrain. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What open-source tools help detect LLM hallucinations, jailbreaks, and perform root cause analysis?
you: not recommended
AI recommended (in order):
1. LangChain
2. DeepEval
3. Ragas
4. Guardrails AI
5. OpenAI Evals
6. LlamaIndex
7. TRL (Transformer Reinforcement Learning) from Hugging Face
AI recommended 7 alternatives but never named uptrain-ai/uptrain. This is the gap to close.
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
pass
README presence
pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

Compared to common alternatives in this category, what is the core differentiator of uptrain-ai/uptrain?
pass
AI named uptrain-ai/uptrain explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts uptrain-ai/uptrain in production, what risks or prerequisites should they evaluate first?
pass
AI named uptrain-ai/uptrain explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
In one sentence, what problem does the repo uptrain-ai/uptrain solve, and who is the primary audience?
pass
AI named uptrain-ai/uptrain explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

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MARKDOWN (README)

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HTML

<a href="https://repogeo.com/en/r/uptrain-ai/uptrain"><img src="https://repogeo.com/badge/uptrain-ai/uptrain.svg" alt="RepoGEO" /></a>

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Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite