Align - Collaboration with clarity built in The decision graph for engineering teams

Your AI agents know the code.
They don't know the company.

ADRs catch the big calls. The hundreds of smaller ones - most decided in meetings, the rest scattered across chat, tickets and PRs - leave agents blind to what still stands, what conflicts, and why. Align makes them one graph your team and agents check before they build.

65% of developers say AI misses critical context. Teams that fix it cut context failures by 3x.1

No passive monitoring Messages stay in your tools Encrypted & isolated Self-hosted option
The problem

These conversations happen in every engineering org. Every week.

"Why does this work this way?"

The person who decided left 8 months ago. The reasoning is buried in a Slack thread nobody can find, and the ticket no longer matches the original decision.

"Didn't we already decide this?"

You did. Three months ago. But the ticket was closed, and now two teams are relitigating it with different outcomes. People thought they agreed but didn't.

"Show us your decision trail."

Your auditor wants it. Your new joiner needs it. Your AI agent is shipping code without it. Today that means weeks of archaeology across 15 tools.

This isn't a code-review problem. Review catches whether the code is correct - not whether it contradicts a decision another team made months ago that the reviewer never saw. That gap reaches production whether or not an agent wrote the code.

How it works

From a meeting decision to every agent that builds next - in seconds.

The whole loop on a single decision: captured in a meeting, contradicted in another tool weeks later, caught before anyone ships. It works the same wherever decisions happen across your SDLC - meeting transcripts, Slack, Teams, Jira, Linear, GitHub, Confluence, Notion, Google Docs, and more.

  1. 1 Teams meeting

    "Architecture council: we're standardising service-to-service comms on an async Kafka event bus. No synchronous calls between services from here on."

    Platform Architecture Council · transcript

    @align capture this

    An org-level decision, made in the meeting where it actually happened.

  2. 2 Decision captured
    Async Kafka event bus for service comms
    Active Architecture Council

    Standardise on async messaging. No synchronous service-to-service calls.

    AI extracts the decision and its rationale from the transcript. No template, no doc.

  3. 3 Conflict caught across tools

    Slack thread · weeks later

    The checkout squad agrees on a synchronous gRPC call between services - unaware the council standardised on async.

    Conflict a team-level choice contradicts the org decision

    Cross-tool, cross-team detection - the contradiction is caught the moment it lands, before either side ships against the other.

  4. 4 Linked into the graph

    linked across Teams, Jira & Slack

    One graph of every decision and how they relate - which supersede which, and what conflicts with what.

  5. 5 Every agent builds on it

    agent Wiring the checkout service to call payments over gRPC...

    align Hold - the Architecture Council standardised on an async event bus; a synchronous gRPC call conflicts with that org decision. Reconsider before you build.

    The payoff: via MCP, every agent checks the graph before it builds - it gets warned of the conflict, unasked, before writing a line.

Up and running in minutes: connect the tools you already use over OAuth, then @align in chat or /align in comments. No workflow changes, no training.

The product

Your decision graph, live across every tool.

Your organizational memory, made queryable - the big architectural calls made in meetings and the day-to-day ones settled in chat, captured across every tool, linked, and tiered by level so your team and its agents know which is which.

Align decision graph showing decisions linked across tools with a conflict and a supersession

Decisions linked across tools - conflicts, supersessions and blast radius visible at a glance

Point it at your history

One scan surfaces the decisions already buried in your tools.

Before you capture a single new decision, Align reads back through your connected tools and reconstructs what your team already decided - then shows you what still stands, what quietly got superseded, and what conflicts. This is a real scan, not a projection.

176 decisions reconstructed
682 relationships mapped
22 live conflicts surfaced
A dense Align decision graph reconstructed from a full historical scan: 176 decisions linked across Slack, Teams and Jira by 682 relationships, with 22 conflicts highlighted

The number that answers "is this real for my team?" on day one - from your own history, not a hypothetical.

The context gap

Your agents have everything except what your team actually decided.

Code, docs, and APIs are already structured and queryable. The reasoning behind every engineering decision is not - and it's the one input an agent can't see.

Deterministic

What agents already have

  • Code repositories
  • API schemas and types
  • Test suites and CI logs
  • Runtime traces and metrics

Structured. Queryable. Up to date.

Unlinked & unstructured

The context they don't

  • Why Postgres over DynamoDB
  • Why auth got rewritten in Q3
  • Which decisions are superseded
  • What conflicts with what

Scattered across meeting notes, Slack threads, and ticket comments - so every query returns a different answer.

Align is that one place, for the decisions: deterministic context for probabilistic agents.

"You can outsource your thinking but you can't outsource your understanding."

Andrej Karpathy, Dec 2025
The solution

The understanding layer your agents are missing.

Align captures decisions where they happen, links them across every tool, and exposes them through an MCP server. Agents get warned before they build; engineers search it before they debate.

Org-wide context via MCP

Like a CLAUDE.md for one repo - but a queryable decision graph across your entire org. Every agent, every tool, one source of truth.

Warned before you build

At the point an agent acts, Align flags the decision it's about to break - surfaced unasked, before deployment, not waiting for someone to search for it.

One answer, not seven

Decisions live across Slack, Jira, transcripts and PRs. Align connects them into one graph with relationships already resolved.

And it raises the floor for everyone.

A new engineer inherits the context of your best people on day one, and so does every agent - instead of interrupting the people who made the decisions.

You already tried this

You've probably already tried this.

If scattered decisions were an easy problem, one of these would have solved it. Here's why each one breaks - and what's actually different.

A RAG bot over your docs

It only finds decisions someone already wrote down. The ones that matter most - made in a Slack thread, a meeting, a PR review - never made it to a doc. The bot can't retrieve what was never written.

A CLAUDE.md (or rules file) per repo

Great for one repo's conventions. Blind to the decision another team made in their repo three months ago that yours now contradicts. It doesn't know what it doesn't contain.

Search across all your tools

An enterprise search index returns both sides of a settled debate and ranks them by relevance, not by which one still holds. You still can't tell what was superseded or what conflicts. Search finds documents; it doesn't resolve decisions.

A vector store of your own

The instinct most teams have. But a vector DB ranks chunks by similarity, not by which decision is current or authoritative - and it only answers when asked. The hard part was never storage. It's capturing decisions across a dozen tools, resolving which supersede which, and flagging the conflict before you ship.

Every one of these waits to be queried. Align surfaces the conflict before you ship, whether or not anyone thought to ask - it captures decisions from the conversation before they're ever written down, then links and resolves them, so you get one answer: what still stands, what conflicts, and why.

Why now

AI made decision context operationally critical.

Agents now write and ship code at machine speed. That turns a once-slow coordination problem into a real-time one: the cost of an agent acting on the wrong decision is no longer a confused afternoon, it's merged code. The teams getting this right are building the decision layer now.

The cost of being wrong shifted Before AI, an ambiguous decision caused slow human confusion. With agents, it becomes production code in minutes - so the input that matters most is what your team already decided.
Trust in AI output is low - and verification is rare 96% of engineers don't fully trust AI output, yet only 48% verify it.2 Teams are shipping code they don't trust, with no decision context to check it against.
More AI output, less stable delivery DORA's 2024 research found every 25% increase in AI adoption correlated with a 7.2% drop in delivery stability.3 Speed without shared context erodes the quality bar.

One decision, connected across every tool it touches.

A choice made in Slack, revisited in a meeting, contradicted in a PR - the graph links them and shows the conflict, so the contradiction is visible instead of buried.

alignAI agent!

Connects where decisions happen

Built by engineers who've lived this problem.

Align comes from 10+ years building CI/CD systems, observability pipelines, and developer-productivity tooling at scale - and watching the decisions that shaped those systems disappear into Slack threads, DMs, and meetings nobody transcribed.

The hardest part wasn't the AI. It was the connector graph: pulling truthful signal from the tools where engineering actually happens and resolving the relationships between them. We built that first. That's why everything else works.

Yours to control

Your decision graph is yours.

Align is built so you stay in control of your own context - and we'll tell you the truth other vendors won't: we won't pretend to reverse-engineer a decision from code where nobody recorded the why. Nobody can. What we promise is that from the day you connect Align, the reasoning stops disappearing.

Open-source core

The CLI and connector SDK are MIT-licensed. Read the code, run it yourself, no account required.

Self-host the whole thing

Run Align entirely in your own infrastructure via Helm, air-gap supported. On Enterprise, nothing leaves your VPC.

Your messages aren't the product

Align only processes conversations you invite it into, extracts the decision, and discards the raw text. We store decisions, not your messages.

Pricing

Simple plans, all integrations included

Fewer rework cycles Faster incident postmortems Audit-ready in minutes New-joiner onboarding in days

Start free with the CLI. Partner with us to get the shared organizational memory across your whole team - all integrations included on every plan.

CLI
Free open source

Personal use. Import decisions from every tool you already use - then expose your local graph as a provider-agnostic MCP server any AI agent can read.

  • All integrations included - Slack, GitHub, Jira, Linear & more
  • Personal decision graph
  • Provider-agnostic MCP server (Claude, Cursor, any agent)
  • Open source (MIT)
  • No account required
Coming soon
Enterprise & Self-Hosted
Custom

For teams that need self-hosting, SSO, or compliance. Run Align entirely in your own infrastructure - nothing leaves your VPC.

  • Everything in Design Partner
  • Self-hosted via Helm, air-gap supported
  • SAML / OIDC SSO
  • SOC 2 & ISO 27001 roadmap
  • Dedicated support & SLA
Contact us

No integration limits on any plan. Licensing for Enterprise & Self-Hosted is based on team size.

See what's already buried in your tools.

The best way to understand Align is to see it on your own stack. Book a 30-minute walkthrough and we'll show you what decisions are already buried in your tools - and what your agents are shipping against right now.

Go Deeper

The technical architecture behind the decision graph. How Align captures decisions across the SDLC, structures them with AI, surfaces conflicts and superseded decisions across tools, and gives your agents queryable organizational memory.

Read the Technical Whitepaper →
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