Koi's Accelerated Modeling Process
Last Updated: 2025-03-12
Koi Engine Overview
Koi offers unrivaled speed and accuracy in model delivery. As the first and only platform to provide on-demand, customized emissions forecasts, it is designed to equip innovators and investors with analytics that accommodate different use cases, timelines, and technologies. Koi models are built on a validated Data Lake that integrates extensively curated, foundational data from reliable sources such as the IEA, SBTi, and Ecoinvent.
Key Concept: The world is complex! We believe pre-computing every combination of technology, intervention type, conventional system, potential baseline, geography, market, etc. is a fool's errand. Koi takes a different approach:
- Rapidly model a reasonable starting point using a consistent methodology.
- Validate and refine models if and when appropriate (e.g. when moving through diligence).
- Produce auditable, versioned models that can contineu to be refined as companies scale.
Using trustworthy emissions baseline and market data as a foundation, Koi's computational engine instantly constructs a climate solution technology model that includes anticipated life cycle intervention points and potential market uptake.
Schematic of the Koi Engine's approach to automated modeling
Integrating Automation into Commissioned Forecasting Services
Koi's modeling approach is designed to accommodate a wide range of analytical needs and climate strategies. All Koi license holders have access to the Data Lake and previously constructed models via the Search Engine. Users can customize models in Koi Studio to incorporate their specific data and modify parameters as desired.
In cases where a solution model does not yet exist, baseline data are missing, or the user has modification requests they prefer not to implement themselves, commissioning a new model may be of interest.
Koi lowers the barriers to obtaining customized, forward-looking emissions models. The status quo entails analysts maintaining bespoke spreadsheets to track reliable data sources (spanning everything from emissions intensities to market sizes). These spreadsheets are most often manually maintained, and act as data libraries for constructing analyses on a case-by-case basis-—often lacking technology specificity and requiring weeks of manual research by specialists. This legacy approach is not only time- and cost-intensive but also prone to errors, difficult to maintain, and ineffective for collaboration. Nevertheless, expert manual review offers substantial benefits and is why we offer a hybrid approach with our expert forecasting services.
Forecasting Services
Forecasting Services are offered in multiple tiers for maximum flexibility across use cases. Every new model begins with the auto-generated draft, which is then reviewed or modified by a trained scientist.
Despite advancements in AI and our meticulous Data Lake curation, we do not currently offer Koi's auto-generated models for purchase without essential quality assurance.
Our fastest option, rapid models, follow the above flow process with the addition of having key parameters checked and refined for accuracy before delivery on the platform. Every model accessible through the Koi search engine for license holders meets this essential quality assurance standard, with some having received additional manual refinements that add significant nuance.
Versioning Every Koi model is versioned. Look for a pill with text like, v1.2: Latest. This is critical for
auditing and is particularly helpful for quarterly and annual reporting as realized impact is compared to the
initial potential impact that you model.
Use Case Considerations
Each use case requires specific considerations of technology nuance and detail.
Some Koi users model the potential impact of early-stage ventures, where significant uncertainty surrounds both the future product and target market. These users often find that rapid models are well-suited to their needs given the inherent uncertainty, the wide range of technologies under consideration, and budget constraints.
Conversely, other users require a deep understanding of potential investment impacts and prefer our higher-tier models, which integrate our scientists' technical expertise through stakeholder engagement and discovery, while still leveraging the efficiencies of automated modeling.
Starting with the auto-generated model, our scientists maximize time efficiency by focusing on the details that matter—-whether it's regional specificity, incorporating insights from white papers or technical reports, or modeling unique lifecycle phases for the solution.
This approach allows for the generation of best-in-class models in a fraction of the traditional time. Further, anchoring models to the foundational Data Lake not only saves precious time but also ensures consistency and data intercompatibility across analyses both now and in the future as the underlying data are updated.
Next steps
- For more information about each model tier, check out the forecasting services pricing table and the informational popups for each feature.
- Allowing users to access autogenerated models and perform their own quality assurance via a guided process is on our Koi Roadmap roadmap. If this is an important feature to you, please consider providing feedback within the roadmap.