Lightning Rod: AI Forecasting API
Predict anything with AI
1.2K followers
Predict anything with AI
1.2K followers
Foresight by Lightning Rod is an OpenAI-compatible forecasting API for developers building forecasting agents, prediction bots, and decision tools. Ask a question about a future event and get a scored, calibrated forecast back. Unlike general-purpose LLMs, Foresight is trained and evaluated on real-world outcomes, with benchmark-verified accuracy, cheaper inference, and a drop-in API for forecasting workflows.
This is the 3rd launch from Lightning Rod: AI Forecasting API. View more
Foresight by Lightning Rod
Launched this week
Foresight by Lightning Rod is an OpenAI-compatible forecasting API for developers building agents, prediction-market bots, and decision tools. Ask a question about a future event and get a scored, calibrated forecast back. Unlike general-purpose LLMs, Foresight is trained and evaluated on real-world outcomes, with benchmark-verified accuracy, cheaper inference, and a drop-in API for forecasting workflows.
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can developers fine-tune forecasts for specific domains like fiance or healthcare?
Lightning Rod: AI Forecasting API
@aleksander_brousseau great question. We do offer fine-tuning via our SDK, although its in private beta at the moment – please reach out if you're curious in giving it a shot.
One big advantage of our Future-as-Label methodology (https://openreview.net/forum?id=vIXPxsiCID) is that we can fine-tune models using the messy, unstructured operational data that companies already have (like docs, reports, patient records, claims, etc) instead of needing labeled datasets to train on. So we regularly train custom models (https://www.lightningrod.ai/custom-models) for clients and we're working on making this more out-of-the-box.
Lightning Rod: AI Forecasting API
@aleksander_brousseau We work 1-1 with enterprise clients for training these types of models. Most organizations sit on mountains of unstructured data full of predictive signal that can we used to forecast verifiable outcomes. Think patient notes, investment decks, CRM content... anything with a timestamp. Shoot me a message if you have a specific usecase in mind
Interesting idea. is there a public demo where developers can try a few forecasts before integrating the API?
Lightning Rod: AI Forecasting API
@rose_florean Yes! Log in at https://www.lightningrod.ai/models and you can run forecasts directly in the UI.
We give new users free credits to play around with, and PHFORESIGHT gets you $50 more this month.
Lightning Rod: AI Forecasting API
@rose_florean As Ben mentioned, you can access our dashboard from https://www.lightningrod.ai/models
Here is a quick demo of our chat playground interface, where you can try the model and see how to integrate it with the API:
Have you compared it against prediction markets directly, or only against LLMs?
Lightning Rod: AI Forecasting API
@ella_reyes1 Yes — we regularly compete on 3rd party benchmarks like ForecastBench and ProphetArena, where we beat frontier models and are evaluated against live market outcomes. We do see an edge in some categories like Sports and Politics. That said, a base forecasting model is just one layer — signals gathering, market timing, bet selection, position sizing all matter too. Foresight gives you a strong calibrated foundation, but sustained alpha in prediction markets requires a differentiated approach on top, like proprietary data sources or novel strategies that can't be easily replicated.
The OpenAI-compatible API shape seems like a smart choice here, because forecasting is often something an agent wants to call inside a larger workflow, not a separate dashboard.
One product detail I’d look for as a developer is whether the calibration stays visible after the API call: confidence interval, data/source freshness, and a short reason why the model thinks the probability changed. For agent workflows, the forecast is useful, but knowing when not to trust it may be even more useful.
Love that this is trained on real-world outcomes rather than just text patterns, making it a purpose-built forecasting layer that general LLMs simply cannot replicate.
Lightning Rod: AI Forecasting API
@ilko_kacharov 100%! We find that general LLMs are pretty bad at forecasting out of the box. Training specifically for forecasting massively improves results and lets us use a smaller model to offer much cheaper / more efficient inference.
how often do you recalibrate the model as new outcomes become available?
Lightning Rod: AI Forecasting API
@maryam_nafees1 We typically update the models every few months, but we actually haven't observed much drift. What we're really training is better reasoning over real-world outcomes, and the model learns to use whatever information is shared in context. So most of the gains don't require the model itself having fully up-to-date knowledge of the world, as long as the right info is in context.
I like that you're tackling forecasting as its own problem instead of assuming a general-purpose LLM is the right tool for everything. An OpenAI-compatible API with lower inference costs also makes it much easier for developers to experiment without reworking their existing workflows. Beyond sports and politics, which real-world forecasting domains have you found Foresight performs especially well in, and are there any areas where you'd still recommend using a frontier model instead?