Independent research. Practical products.

Understand
the market.
Find your range.

Market analytics for the tools you build. Liquidity management for the positions you hold. Two products, built on the same research.

Explore our products Discuss a pilot

Built from hands-on experience in digital asset markets.

Llama Analytics / Market viewIllustrative example
SUI / USD · Market context
Read the conditions.Transition
Earlier observationsLatest observation →
01 / REGIMEMarket conditions
02 / VOLATILITYPrice variability
03 / MEAN REVERSIONOU diagnostics
Context before action.

Analytics inform. Portfolio controls decide.

ONE RESEARCH FOUNDATIONMarket dataAnalytics & forecastsTools for different decisions
Our products

One foundation.
Two ways to use it.

Build with our market insights, or explore how we apply them to liquidity management.

01 / FOR DEVELOPERS & RESEARCHERSAPI in development

Llama Analytics API

A consistent view of market regimes, volatility and mean reversion, with forecast trends and familiar technical indicators.

// Market context, ready for your application
regime : "transition"
volatility : { lookback: "1h", … }
mean_reversion : { fit_valid: true, … }
Explore the API
02 / FOR LIQUIDITY PROVIDERSNew learner in shadow evaluation

RangeKeeper

Liquidity management software connecting range decisions, exposure controls and hedge coordination in one workflow.

Liquidity positionReserveHedge collateral
Conceptual allocation · not a recommended portfolio
Explore RangeKeeper
Built with context

A number tells you what.
Context helps with why.

Markets change character. A trend indicator, a volatility estimate and a forecast each describe a different part of the picture.

We bring those observations together, with their timing and limitations, so they can be used thoughtfully.

  1. 01

    Understand the conditions

    Distinguish current market behaviour from a forecast of what may happen next.

  2. 02

    Know when an estimate is usable

    Quality checks and model-fit diagnostics help identify when an output should not be relied on.

  3. 03

    Choose how to act

    Use the API in your own application. Explore RangeKeeper for a separate portfolio-management workflow.

Our story

Built from the questions that come with managing your own positions.

Research rooted in practical experience.

From Llama Analytics
to RangeKeeper.

RangeKeeper grew from the founder's experience managing personal funds and researching markets at Llama Analytics.

Working with concentrated liquidity raised questions about range selection, changing exposure and when to reassess a position. Those questions shaped our research and the software we are building.

The analytics API opens a broader path: making selected market insights available to developers and researchers, independently of our trading strategy.

Let’s build from here

What are you working on?

Tell us about your data needs or liquidity workflow. We’re interested in conversations with early users and pilot partners.

Discuss a pilot support@llamanalytics.com