Lightning Rod: AI Forecasting API
Predict anything with AI
839 followers
Predict anything with AI
839 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
Launching today
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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Launch Team
Lightning Rod: AI Forecasting API
Hey Product Hunt — Ben here, founder of Lightning Rod Labs.
Frontier AI is powerful, but it is not built for forecasting. Frontier models are trained to produce plausible text, not well-calibrated probabilities about what will actually happen. They are also expensive to run inside agentic workflows, where bots may need to forecast thousands of markets, events, or decisions.
We trained Foresight to make better predictions at lower inference cost.
Foresight is an AI forecasting API with better accuracy at a lower inference cost. It is trained using our Future-as-Label method (Spotlight at the ICML 2026 AI Forecasting Workshop), which uses real-world outcomes over time for training. Instead of hand-labeling datasets or imitating generic text, Foresight learns from what actually happened.
Foresight beats frontier models 100x larger on live prediction benchmarks, like ProphetArena and ForecastBench, with a particularly large lead in prediction market categories like Sports & Politics.
Our API is OpenAI-compatible, so developers can easily swap it into existing workflows.
Better accuracy. Cheaper inference. OpenAI-compatible API.
Use code PHFORESIGHT for $50 free API credits this month.
We'd love feedback from builders working on forecasting agents, prediction tools, or any workflow where better forecasts matter.
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@bturtel Congrats on the launch, Ben. A forecasting API actually benchmarked on real-world outcomes is rare — most AI tools claim predictive power with no calibration to back it. Purpose-building it for agents and prediction markets, accurate and cost-effective, is a sharp wedge.
One idea while it's live: your PH launch is still editable, and a video in the gallery holds attention better than screenshots. So I made you one from your site, free, and it's whitelabel — yours to post as your own: https://foxplug.com/v/foresight-by-lightning-rod-5f375d9f
I build FoxPlug — it turns your real product updates into videos, posts, and GIFs automatically: guided feature tours, GIFs, short posts for X, long-form for a blog, and full product walkthroughs. foxplug.com — building in public, loudly.
Lightning Rod: AI Forecasting API
@saulfleischman agreed! We think forecasting is a powerful benchmark for AI generally–it requires a deep understanding of how the real world works, and it's impossible to hack since the outcomes haven't happened yet.
Cool video!
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.
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 calibration angle is the part that actually matters, and the part most forecasting tools skip. When we plugged raw LLM probabilities into a decision loop, the point estimates were fine but the confidence was wildly off at the tails, so the expected-value math downstream was garbage. Two things I'd want to know: do you return a calibration band or just a point probability, and how does calibration hold up under regime shift, when the future stops resembling the outcomes you were scored on?
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.
The OpenAI-compatible interface is the right call. It means teams can drop this into existing agent pipelines without touching their orchestration layer. We've hit the same problem with general LLMs hallucinating probabilities. They'll say '70% chance' with no calibration behind it. How do you handle calibration drift as events resolve? Is accuracy validated continuously against a live benchmark, or is it a periodic evaluation cycle?
Lancepilot
Lightning Rod: AI Forecasting API
@odeth_negapatan1 thanks, we agree!