AI Clearing vs Superluminal

AI Clearing connects design and BIM data, schedules, budgets, drone imagery, mobile inputs, and ground surveys into one construction intelligence system for large-scale infrastructure and renewable energy projects. Contractors and asset owners use its CORE platform to see what is actually happening on site instead of relying on scattered spreadsheets and field notes.

A proprietary computer vision engine trained on millions of construction objects compares as-built conditions against design plans. The platform delivers progress and quality reports within 6 to 24 hours of data capture and includes Clara, a conversational assistant that answers project questions from live field data.

Where most construction software tracks tasks in spreadsheets, AI Clearing is built around visual site evidence. It reconciles drone imagery, schedules, and BIM models automatically, which makes it better suited to utility-scale earthworks and renewables than generic project management tools that lack geospatial progress verification.

General contractors, EPC firms, and asset owners working on renewables, transmission, wind, highways, pipelines, railways, and civil earthworks use AI Clearing for progress tracking, quality control, billing verification, and portfolio oversight. Customers include PCL Solar, baywa-re, and Rosendin Renewables.

Superluminal adds a conversational copilot to product dashboards so end users can ask questions about their data in plain language. You integrate it through a React component or REST API, and it writes Python behind the scenes to filter tables, pivot results, plot charts, and return answers grounded in the dataset already loaded in your app. The target customer is a SaaS team that wants ChatGPT-style data chat without building code generation, sandboxed execution, and prompt tuning in house.

Generic chat widgets summarize text. Superluminal is built specifically for tabular dashboard data: it spins up managed compute to run generated Python, verifies code through reflection, and returns structured answers or charts tied to the user's actual rows. That pipeline (context synthesis, chain-of-thought reasoning, secure execution, and UI customization) is the product, not a thin wrapper around a single model call. It also supports multilingual queries and optional filtered or pivoted views of the underlying data.

Superluminal fits analytics vendors, internal data teams, and any product with an embedded dashboard that wants self-serve exploration. Pricing is pay-as-you-go at $20 per 100 messages after 50 free messages, with enterprise plans for higher volume. Data is encrypted in transit and at rest, purged after each session, and not shared with third-party LLM providers per the company's security page.