Foresight by Lightning Rod vs Selvedge

Foresight by Lightning Rod and Selvedge are both inference engines & infra tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Foresight by Lightning Rod

The product is a forecasting API — you send a question, it returns a calibrated probability. The public Foresight Models are trained on world news and cover sports, politics, and market outcomes; the vendor states these small models out-predict frontier models at lower inference cost. The API is OpenAI-compatible, so swapping it into an existing pipeline is a config change, not a rewrite. The ceiling appears when your domain diverges from world news: at that point, the public models have no grounding in your data, and accuracy degrades against a purpose-trained competitor. The path forward is the enterprise custom model track — which requires a sales call, not a dashboard toggle.

Selvedge

Selvedge is a local MCP server that AI coding agents (Claude Code, Cursor, Copilot) call as they work, logging the reasoning behind every change into a SQLite file that lives next to your code under .selvedge/. Queries are entity-scoped — you ask about users.email or deps/stripe, not line numbers — so the answer surfaces in the same terms you search in. The vendor describes zero telemetry, no accounts, and no external servers; everything stays on disk. The wall appears when your team needs cross-repo provenance or wants to pipe this data into an existing observability stack — Selvedge emits records but does not integrate with those systems out of the box.

Attribute	Foresight by Lightning Rod	Selvedge
Pricing	Paid	Free
Free trial	No	No
Open source	No	Yes
Has API	Yes	No
Self-hosted option	No	Yes
Platforms	—	Linux, macOS, Windows (via Python)
Released	—	2026-05
Pros	Calibrated probability outputs rather than confident-sounding guesses from a general model, which means downstream decisions based on forecast confidence are grounded in a model trained specifically to get probabilities right. OpenAI-compatible API surface, so existing agents or applications already calling OpenAI can route forecasting queries here with a one-line config change instead of a structural rewrite. Built-in research mode on the public models, which means the model can surface supporting context alongside its probability estimate instead of returning a number with no audit trail. Custom model track trains on your proprietary data and deploys in your cloud, which means organizations with sensitive internal data are not forced to expose that data to a shared inference endpoint. Small, task-specialized models running at lower inference cost per call than frontier models, which means forecasting at volume does not carry the same API bill as routing every query through GPT-4-class infrastructure.	Reasoning is captured in the same context window that produced the change — not reconstructed from the diff afterward — which means the intent survives even when the original prompt, the developer who wrote it, and the model version are all gone. Entity-scoped queries (selvedge blame payments.amount, selvedge diff users --since 30d) let you ask about the things you actually search for rather than hunting through line-level history, so a schema audit that would take an afternoon takes a single command. Fully local storage in a SQLite file with no accounts, no telemetry, and no external servers, which means sensitive schema and API change history never leaves the machine — a hard requirement in compliance-heavy environments. Provider-agnostic MCP integration wires into Claude Code, Cursor, and Copilot through a single setup command, so teams already using any of those agents get provenance logging without changing their workflow. Full-text search across all logged events (selvedge search "stripe") and changeset grouping (selvedge changeset add-stripe-billing) mean you can reconstruct the full scope of a feature build after the fact, which is the audit trail that git log alone cannot provide.
Cons	The public Foresight Models are trained on world news, so forecasting questions rooted in proprietary, internal, or niche-domain data return predictions with no relevant training signal — teams with those use cases either move to the custom model track (which requires an enterprise sales engagement) or switch to a competitor that allows self-serve fine-tuning on uploaded datasets. There is no self-hosted deployment option for the public API, which means every inference call passes through Lightning Rod's infrastructure — for regulated industries with data residency requirements or air-gapped environments, this is a blocking constraint that no configuration change resolves. The custom model path requires booking a call rather than provisioning through a dashboard, so teams that need to prototype a domain-specific forecaster inside a sprint timeline cannot self-serve — they are gated on a sales cycle before they can test whether the custom model actually outperforms what they already have.	Selvedge has no API and no export integration — teams that need to push reasoning records into an existing compliance platform, a data warehouse, or a centralized observability system must write their own pipeline against the SQLite file, adding a maintenance surface that grows with audit requirements. The store is scoped to a single local project directory; teams running multi-repo codebases where an agent change in one repo depends on a change in another get no cross-repo provenance, and at that point teams managing compliance across repositories will move to a dedicated audit-log solution that operates at the organization level. Selvedge only captures what the agent explicitly logs through the MCP tool call — if an agent skips the log_change call, makes changes outside a supported tool, or the MCP connection drops mid-session, that change has no recorded reasoning and the gap is invisible in the history.

Bottom line

Foresight by Lightning Rod is paid while Selvedge is free; Selvedge is open source; only Foresight by Lightning Rod exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Foresight by Lightning Rod and Selvedge?

Foresight by Lightning Rod is Paid, while Selvedge is Free and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Foresight by Lightning Rod better than Selvedge?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.