Captures while work is live
Syncora listens to live AI and developer work before the rationale evaporates, so the durable parts are captured while the task is still active.
From scattered to structured
Context, pulledinto structure.
Syncora turns scattered context into structure you can return to.
Why It Breaks
Important context does not stay assembled on its own. Decisions, rationale, and constraints scatter across chats, files, and time until the work loses its center.
The Core
A centerfor what matters.
Syncora gives important context a point of gravity. Decisions, rationale, and constraints stay gathered around the work instead of scattering across tools, files, and time.
SYNCORA
architectural memory for ai-assisted codebases
Powered by Model Context Protocol
Works perfectly where you already work.
Cursor
VS Code
Windsurf
JetBrains IDEs
Neovim
Codex
Claude Code
Cursor Agent
OpenAI
Anthropic
Gemini
Terminal
Local LLMs
Cursor
VS Code
Windsurf
JetBrains IDEs
Neovim
Codex
Claude Code
Cursor Agent
OpenAI
Anthropic
Gemini
Terminal
Local LLMs
Cursor
VS Code
Windsurf
JetBrains IDEs
Neovim
Codex
Claude Code
Cursor Agent
OpenAI
Anthropic
Gemini
Terminal
Local LLMs
00 / The Problem
Important context doesn't vanish.It decays into residue.
Large context windows preserve traces, not working clarity. As conversations grow, decisions compress into shorter summaries, losing rationale, scope, and rejected alternatives until they no longer map cleanly to the code they govern.
Decision lands
Choice + rationaleDefinition fully legible
"Syncora is an autonomous memory orchestration layer for AI-assisted coding. It captures durable decisions, facts, rejected options, and rationale from chat and attaches them to files, symbols, components, and other code anchors. It retrieves only the context relevant to the current edit, stores settled decisions before code changes, treats code changes as corroboration rather than a requirement, and escalates only ambiguous or risky cases."
usable context
100%
Conversation grows
~180,000 tokens laterRetrieval model intact
"Syncora captures durable coding context from chat, links it to code anchors, and retrieves the relevant decisions, rationale, and rejected options for the current edit. It can store settled decisions before code changes, use code changes as corroboration, and escalate only ambiguous cases."
usable context
82%
Threads overlap
~950,000 tokens laterBoundaries still readable
"Syncora captures chat decisions and rationale, links them to code, and brings back relevant context during edits. Code changes strengthen confidence, but capture can happen before code exists."
usable context
61%
More edits, less shape
~3.6M tokens laterDifferentiation blurring
"Syncora stores important chat context for code and retrieves it when that code changes. It links decisions to code anchors and runs mostly in the background."
usable context
34%
Context residue
~11.4M tokens laterStill true, no longer sufficient
"Syncora stores context for code."
usable context
7%
Important decisions do not disappear. They decay into unusable context.
The model may retain the topic.It loses the operating definition.
01 / Same Task / Better Starting Point
Same task.
Very different starting point.
Without Syncora, context lives in fragments around the repo. With Syncora, it becomes working memory attached to the task, the code surface, and the next edit.
Chat fragment
Capture the reasoning before code lands if the direction is already settled.
Code anchor
Bind it to files, symbols, or broader scopes so retrieval starts near the work.
Loose rationale
Prefer over-capture when retrieval stays scoped to the task.
Scope note
Code changes raise confidence, but they are not required for capture.
Rejected path
Do not keep only final decisions. The rejected path matters later too.
Confidence gap
Capture confidence, binding confidence, and finality are separate signals.
Open question
Which context is durable enough to survive into the next edit?
Fragmented context
Fragments. No operating model.
ADR-001 / Syncora working memory record
Externalize working memory around the codebase
A durable record the next AI can query, inspect, and reuse instead of reconstructing the same reasoning from fragments.
Status
Accepted
Updated
2026-03-23
Updated by
Founder
Type
Architectural decision
Decision
Preserve durable context around code anchors instead of relying on approvals or fragile model memory.
Retrieval scope
Pull only the memory packet, code anchors, and rejected paths relevant to the current edit.
Rationale
The next AI needs reasoning, constraints, and rejected paths before it touches code.
Constraints
Capture can happen before code lands. Human review is the exception path for ambiguity, conflict, or risky changes.
Code anchors
files, symbols, components, and broader task scopes when the work spans more than one surface
Rejected path retained
Approval-only memory and final-decision-only capture leave too much useful context behind.
Source trace
Live chat capture, scoped retrieval policy discussion, and linked implementation notes from the same decision window.
Working set
Code-linked memory
Scoped retrieval
Rejected paths kept
Ready for next edit
Operating brief
Usable context before the next edit starts.
02 / The Capture Layer
Important decisions,
captured before they dissolve.
Syncora listens to the live session, extracts the decisions that matter, preserves why they were made, and attaches them to the code they should govern.
conversation
extracted memory
attached to code
What mattered in the conversation is now durable, structured, and in scope for the next edit.
03 / The Maintenance Layer
Code changed elsewhere.
Syncora knows what just went stale.
A git diff without attached session context is enough to flag stale memory, lower confidence, and queue a rationale refresh. It is not enough to invent the new reasoning.
origin/main - remote diff - no session trace
waiting for remote diff...
Syncora - attached memory maintenance
awaiting affected anchor
waiting for the scan to reach the changed capture policy lines before loading the attached packet
anchor unresolvedwaiting on scan
unaffected packet
unrelated memory stays out of the check until the affected anchor is resolved.
refresh rationale
Recover the new why before promoting fresh memory
Space is reserved for the rationale refresh request once Syncora proves the attached memory is stale.
2 attached packets - all trusted
The fear
"A teammate changed the code somewhere else, so Syncora will probably invent a fake explanation and attach it forever."
The reality
Git diffs retire stale memory. Fresh rationale still needs real context.
04 / The Memory Graph
Every node carries the operating detail behind the code.
Syncora links ADRs, decisions, constraints, rejected paths, code anchors, and maintenance signals into inspectable memory bundles.
Drag the graph, hover to trace relationships, and click any node to inspect the attached memory bundle behind that code decision.
Decision, rationale, and constraints
Rejected path and code anchors
Source trace, staleness, and refresh state
The difference
Same question.
Very different answer.
A new chat only knows what is in the window.
New chat - no previous contexthonest limit
New chat - Syncora fetchretrieved on request
The model is the same.
Syncora changes what the model can retrieve on demand.
Features
What makes that
answer possible
The replay works because Syncora is not just storing notes. It is capturing, anchoring, retrieving, and maintaining operating memory around the code.
Retrieves prior decisions on request
Syncora fetches the exact prior decision into a fresh chat when the model asks for it, instead of pretending the new window remembers last week.
Anchored to code
Syncora binds memory to files, symbols, and code anchors, so retrieval lands on the exact surface that the decision governs.
Stale memory gets flagged
Syncora flags when incoming diffs conflict with stored memory, so stale rationale is surfaced before a model reuses the wrong context.
Rationale stays attached
Syncora keeps the chosen path, constraints, and rejected alternatives together instead of leaving only a diff and a vague memory of why.
Portable and private
Bring your own model keys while keeping the memory layer portable through MCP, without training on your repo or pooling your data across users.
FAQ
Questions before
you trust it
The product story is simple once the objections are answered directly.
Syncora captures durable decisions, rationale, constraints, and rejected paths while the work is still live, instead of waiting for someone to remember what mattered after the task is over.
Review is reserved for ambiguity, weak anchors, or risky changes. Routine context can be captured automatically when the signal is strong and the binding is clear.
Yes. Syncora can fetch the prior decision into a fresh chat before the model answers, so the new session does not need the old transcript pasted back in manually.
Syncora will mark existing memory stale and queue a refresh instead of inventing new rationale from the diff alone. The change is treated as strong evidence that old memory may be wrong, not proof of the new reasoning.
You bring your own model keys, and Syncora keeps the memory layer under your control. The product is designed so you can preserve the context boundary instead of donating repo memory to a shared model pool.
Adoption is meant to be low-friction. Syncora watches the work already happening across your editor and AI sessions, so the goal is to add memory infrastructure without forcing a second documentation workflow.
Any MCP-compatible client can retrieve from Syncora. The memory layer stays portable through MCP, so the same operating context can travel across the tools your team already uses.
Pricing
Start free, scale only
when context becomes critical.
Syncora is priced for individual adoption first. Start free, then move to Pro once the memory layer becomes part of your daily coding loop.
Free
Run Syncora in your editor, prove value on real code, and build durable working memory without paying up front.
- 1 user, unlimited projects
- BYOK model access
- Background capture and scoped retrieval
- MCP traversal and query access
Pro
For individual developers who want the full Syncora memory layer active on real codebases without a sales conversation in the loop.
- Deeper retrieval and richer memory inspection
- Stale-memory maintenance and refresh queue
- Node history and recovery
- Graph export and improved retrieval quality
Team rollout is deferred to V2 while the live product stays focused on solo-first adoption.