FLASH

How it works · Hardware context engine

Turn your board, code and device evidence into structured AI context.

The context engine is the layer under every Flash surface. It reads your schematics, datasheets, SDK, build output, and live board state, and turns them into a compact model the agent can reason over — before a single token is spent.

What goes in

01

Schematics

KiCad, Altium, netlists — pins, nets, buses.

02

Datasheets

Registers, bit fields, and timings, with citations.

03

SDK & toolchain

HAL surface, build system, and pin map as configured.

04

Build output

Compiler diagnostics, map files, and flash/RAM budgets.

05

Board state

Serial traces and runtime signals from the real target.

What it builds

Board model

Peripherals, buses, clocks, and memory resolved to your exact part — not a family average.

pinsnetsclocksmemory

Firmware model

Your tree, targets, and drivers indexed statically — so changes land where the project expects them.

symbolstargetsHAL calls

Evidence index

Every fact traced back to a page, a net, or a log line — auditable instead of asserted.

citationsprovenance

Example context trace

An illustrative ESP32-C6 project includes a schematic, an ESP-IDF source tree, a BME280 datasheet and the latest build output. Flash resolves those inputs before the agent sees the task.

Board model
ESP32-C6, I²C0, BME280, resolved pins, voltage domain and bus membership
Firmware model
Build target, component tree, existing I²C symbols, configuration and toolchain
Evidence selected
Relevant nets, source symbols, datasheet sections and current compiler diagnostics

This trace explains structure, not a benchmark. Quantitative model comparisons remain unpublished until the test setup and results are reproducible.

Why it matters

A model that doesn't know your board can only guess at your board.

Context is built by static analysis, not by a language model summarising files. It is reproducible, it fits in a fraction of the tokens raw sources would need, and it can remain inside your network. That gives a smaller local model a focused set of relevant engineering evidence instead of an unfiltered repository dump.

Go deeper

Point it at
your board.