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zynoptes.

Stop developingin the dark.

Zynoptes is an optimization engine that reads your entire codebase at once and finds the critical optimizations that live between files.

scans the whole repository at oncecross-file reasoning · trace depth 7every optimization ships its evidence chaincomplexity, memory & hot-path passesthe intelligence is in the harnessscans the whole repository at oncecross-file reasoning · trace depth 7every optimization ships its evidence chaincomplexity, memory & hot-path passesthe intelligence is in the harness
The blind spot

The slowdown isn'tin a file. It's between them.

01

Two files. Each one passes review.

A motion-estimation loop and a frame-pool helper, three modules apart. Read alone, both are textbook-clean.

codec/motion_est.c
✓motion_est.c · clean
1static int me_score_frame(MECtx *ctx, FramePool *pool) {
2 for (int mb = 0; mb < ctx->mb_cnt; mb++) {
3 Frame *ref = pool_get_frame(pool, mb);
4 for (int d = 0; d < 16; d++)
5 ctx->score += block_sad(&ctx->blocks[mb], ref, d);
6 pool_put_frame(ref);
7 }
8 return ctx->score;
9}
codec/frame_pool.c
✓frame_pool.c · clean
1Frame *pool_get_frame(FramePool *p, int idx) {
2 Frame *f = &p->slots[idx & SLOT_MASK];
3 if (f->gen != p->gen) {
4 f = refresh_slot(p, idx);
5 }
6 /* defensive copy, “almost never” taken */
7 f->refcount++;
8 copy_frame(&f->cache, f->raw, FRAME_BYTES);
9}
critical · hidden memcpy on the hot path
zynoptes optimization #001critical

Full frame copy in the macroblock loop

pathpool_get_frame → copy_frame → per macroblock
zero-copybroken on every call
files2 files · codec/ · trace depth 4
Impact: a full frame copy per macroblock. The encoder's hottest loop lives in memcpy. Evidence chain attached.
0

valid optimizations surfaced on a sandboxed FFmpeg in hours. 30 matched commits the maintainers later accepted.

The harness

Four passes. Zero guesswork.

01 INGEST02 LABEL03 SEGMENT04 ANALYZErepo →auth/net/codec/sched/db/ctx 01✓ctx 02✓ctx 03✓ctx 04✓ctx 05✓VERIFY

Ingest. The whole repository, not a sample. Every file lands in a structured graph model: dependencies, callers, data flow.

Why now

AI writes most new code now, and nobody optimizes it. Deep optimization used to need a frontier lab. We built the harness that gets it from public models: whole-repo reasoning, focused context, optimizations that arrive verified. The intelligence is in the harness.

What it finds

Optimizations that needthe whole system.

The speed you only catch by reading everything.

optimizations — live queue
CRITICAL2 files · codec/ · trace depth 4
motion_estme_score_frame()frame_poolcopy_frame()zero-copybroken ✕a full frame copy honored on every callthe encode path lives in memcpy

Hidden memcpy on the hot path

A frame-pool helper defensively copies a full frame inside a per-macroblock call. The encoder's hottest loop spends its life in memcpy.

evidencepool_get_frame → copy_frame → per macroblock · full frame copy
Pricing

Connect a repo.Priced to fit it.

Every engagement analyzes your whole codebase and backs every optimization with evidence.

Every codebase

Let's talk

Quoted from repo size, complexity, and usage — no rate card, no procurement cycle.

  • Whole-repo optimization workflow
  • Complexity, memory & hot-path passes
  • Every optimization ships its evidence chain
  • Continuous re-analysis on merge
  • First results in hours
  • VPC / on-prem available

Monthly or annual · cancel anytime

FAQ

Fair questions.

Profilers show you hot symbols one run at a time; linters pattern-match one file at a time. Zynoptes builds a graph model of your entire repository and has frontier models reason across it, surfacing the cross-file, algorithmic inefficiencies that no per-file rule or single profile can express. Most teams run both.

Turn the
lights on.

See what's been slowing you down all along.

founders@zynoptes.com