About Evaligo

What Evaligo does

1. Step 1

   Build

   Describe a workflow in one sentence, or start from a template, and Evaligo lays it out as connected nodes: prompts, agents, tools, web scraping and data steps. Every node stays editable on the canvas.

2. Step 2

   Test

   An experiment runs several variants of the same flow on the same dataset: other models, other prompts, other settings. AI judges score each output against your rubric without knowing which variant wrote it, and the scoreboard shows score, cost per output and latency.

3. Step 3

   Route

   A finished experiment can train a router that picks a model per input. It is evaluated on the experiment’s own samples with 95% error bars, and it runs in the next experiment like any other model.

4. Step 4

   Ship

   Any flow deploys as an authenticated REST API with generated documentation, so the version that won the test is the version your product calls.

Models

Flows and experiments can use models from OpenAI, Anthropic and Google Gemini, and open-source models such as DeepSeek, Kimi, MiniMax and Qwen through OpenRouter. Judges can be a single model or a panel of models from different vendors whose scores are averaged.

What we publish

We run our own experiments on Evaligo and publish the scoreboards, the judges and the cost of each run.

• A Router Trained on 63 Product Listings Matched Claude Sonnet 5 at 4% of the CostFour models localized 63 listings into seven languages. A router trained on that scoreboard then scored 0.909 on 28 unseen listings, Sonnet 0.911, at $0.00033 versus $0.00885 per listing.
• Six AI Models Rewrite 30 Cringe Dating Bios, Scored by Three JudgesSix models, the same 30 deliberately bad bios, three blind AI judges. gpt-5.6-luna scored highest at $0.00056 per profile. The full scoreboard, per judge.
• The Expensive AI Apologized Its Way Out of a Raise — Then Its Newest Version Fixed ItWe had three budget AI models negotiate 30 job offers (nurse to staff engineer, hourly to $200k+), scored blind by an AI judge. gemini-3.5-flash finished last for apologizing too much — then 3.7-flash fixed the tone and jumped to second. The cheapest model still won every axis.
• One Agent, an Assembly Line, or Agent + Editor? We Built the Same AI Agent 3 WaysDoes architecture matter more than model choice? We built the same Reddit-posting agent three different ways, ran 8 model mixes through a 14-criteria AI judge panel, and the most expensive configuration lost twice. Here is the full scoreboard.
• Which AI Model Should Write Your Reddit Posts? We Tested 6 CombosReddit rewards value and bans self-promo. We built a flow that turns your content into community-ready posts in two stages — write, then fix for the rules — and benchmarked 6 model combos on quality, rule-compliance, and cost. Here is the scoreboard.

Who builds it

Evaligo was founded by Danny Lev, who leads the company as Founder & CEO. For questions, partnerships or support, use the contact page.