Engineering Intelligence for the AI era

Software should
explain itself.

Helix connects code, decisions, incidents, ownership, and AI-generated changes into a living Engineering Graph—so teams understand why software exists, what a change affects, and whether it is safe to ship.

GitHub-first. Evidence-backed. Built for teams shipping with AI.
PR #284INC #52RFC 18

AI can generate software faster
than teams can understand it.

Helix closes that gap.

THE QUESTIONS

Every change should answer
three questions.

01

Why does this exist?

Trace code and dependencies back to the pull requests, incidents, documents, and decisions that introduced them.

Explore
02

What will this affect?

See the services, APIs, tests, owners, and business systems connected to a change before it reaches production.

Explore
03

Can I trust it?

Review facts, inferences, risk signals, historical context, and evidence paths in one place.

Explore
THE ENGINEERING GRAPH

Your software is
more than code.

It is years of decisions, dependencies, incidents, reviews, people, and production outcomes.

Helix continuously connects those signals into a living Engineering Graph.

HELIX / PRODUCTION7 ENTITIES · 6 RELATIONSHIPS
EVIDENCE PATHRedis← introduced by —PR #284— resolved →Incident #52
HELIX ASK

Ask why.
Get evidence.

Answers are only useful when you can verify them. Helix shows its work—down to the pull request, incident, decision, service, or metric.

HELIX ASK⌘ K
YOU

Why do we use Redis?

HELIX · ANSWERED FROM 5 SOURCES

Redis was introduced through PR #284 after Incident #52 caused database saturation during login spikes.

RFC-18 proposed moving session reads from Postgres into Redis. Authentication latency dropped from 230ms to 31ms after deployment.

Redis is currently used by Authentication, Rate Limiting, and Checkout.

Verified fact Inference Recommendation
SOURCES
ENGINEERING DNA

Every engineering team
has its own DNA.

Your architecture, review habits, deployment patterns, ownership, incidents, and successful practices make your team unique.

Helix learns those patterns from your engineering history—not generic internet advice.

AUTHENTICATION PATTERN16 PULL REQUESTS ANALYZED

In 14 of the last 16 authentication pull requests:

1Integration tests were changed14 / 16
2A Platform engineer reviewed the change15 / 16
3A canary deployment was used14 / 16
!
PATTERN BREAK DETECTEDThis pull request breaks that pattern.
RECOMMENDATION

Add integration coverage and request Platform review.

PRODUCT SURFACES

One intelligence layer.
Everywhere engineers work.

01
PR #302 · authentication/session.tsRISK · BLAST RADIUS · INCIDENTS · OWNERSHIP · TESTS

Helix Review

Engineering context inside every pull request.

Explore Helix Review
02
HELIX / LIVE CONTEXTWHY DOES THIS EXIST? · WHAT DEPENDS ON THIS API?

Helix Ask

Ask questions about your system in plain English.

Explore Helix Ask
03
HELIX / LIVE CONTEXTPR #284 → REDIS → AUTHENTICATION

Helix Graph

Explore how code, decisions, people, and outcomes connect.

Explore Helix Graph
04
HELIX / LIVE CONTEXT{ "owners": ["platform-team"], "risk": "medium" }

Helix API

Give coding agents and internal tools trusted engineering context.

Explore Helix API
HOW IT WORKS

Helix works where engineering
decisions happen.

01Connect GitHub
02Build the Engineering Graph
03Open a pull request
04Receive engineering context
05Review evidence
06Ship with confidence
07Helix learns from the outcome
INTEGRATIONS

Connect the tools your
team already uses.

Start with the source of engineering change. Expand the graph as Helix adds more trusted signals.

GIGitHubAVAILABLE IN PRIVATE BETA
GIGitLabPLANNED
LILinearPLANNED
JIJiraPLANNED
SLSlackPLANNED
DADatadogPLANNED
PAPagerDutyPLANNED
OPOpenTelemetryPLANNED
NONotionPLANNED
COConfluencePLANNED
CORE PRINCIPLES

Built for engineering truth.

01

Evidence over guesses.

Every important claim links back to its source.

02

Systems over files.

Understand relationships, not isolated artifacts.

03

Context before automation.

Know the system before asking it to change.

04

Facts before inference.

Clearly separate what is known from what is learned.

05

Trust must be earned.

Confidence is visible, inspectable, and grounded.

PRIVATE BETA

Help shape the future of
Engineering Intelligence.

We are working with engineering teams using AI to ship real production software.

Understand your Engineering DNA.
Build with context. Ship with confidence.
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