An operating layer for documents

Spreadsheets did this for numbers.
CorpusWire does it for your documents.

Makes them legible.
Makes them queryable.
Makes them compound.

Your documents are the richest data your business produces — and they've never been usable as data. Until now.

Built in use

The operating system MoreResults built to run our own business. Now available to yours.

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BRAIN · /admin/graph LIVE · 2,841 nodes
"Your business documents, rendered as a queryable intelligence layer."
02Transformation

Three steps to documents that compound.

Step 01
HAND OVER

Hand over what you already produce.

Briefs, SOPs, project notes, decisions, lessons learned, client correspondence. No new work. No new tools to learn. The documents your business already generates are the input.

Step 02
INDEXED · QUERYABLE · ON YOUR STACK

They become a connected intelligence layer.

Indexed, queryable, on your stack. The whole record of how your business actually works — finally legible to the AI tools you already use every day.

Step 03
CONTEXT PULLED

Compounding starts.

Every AI conversation pulls from it. Every new project adds to it. The next hire onboards from a living system instead of from your calendar.

03Interest · Part 1

CorpusWire doesn't create new work. It captures the value of the work that was going to happen anyway.

What changes when your documents start working for you.

01

Every project makes the next one easier.

Past decisions, past lessons, past client work — pulled into context automatically. Your AI gets sharper every week. Not because the model changed, but because your context did.

02

Your SOPs stay current.

Generated from real work. Kept current as the work changes. Available to anyone the moment they need them. No more documents that describe how you used to operate.

03

Institutional knowledge stops walking out.

Every project closes with its lessons captured. Every key decision is retrievable months later. When someone leaves, what they knew stays.

04

You stop being the bottleneck.

New hires onboard from a working system instead of from your calendar. Junior team members produce senior-quality work because the context is in the room with them.

05

The AI tools you already use stop giving generic answers.

Claude, ChatGPT, whatever your team uses. No new interface to learn. The difference is the answers come from your business, not from the internet.

04Interest · Part 2
What CorpusWire does

Five components. One operating layer.

Each component delivers one or more of the benefits above. Together they form an intelligence layer that lives on your infrastructure.

F · 01The Brain

The Brain — your documents indexed as an intelligence layer.

Hybrid search across the whole record — semantic and keyword combined. Heading-aware chunking that preserves structure. Real-time ingestion as new work happens.

Delivers benefits 01  ·  05
brain.admin · index
DOCUMENT CHUNKS UPDATED brief-2026-Q1.md 42 2m ago lesson-learned-08.md 18 3h ago sop-content-qa-v3.md 27 yesterday decision-pricing-tier.md 9 2d ago client-acme-brief.md 61 3d ago retro-2026-04.md 15 5d ago project-notes-mor913.md 33 6d ago 2,841 DOCS · 12,947 CHUNKS · HYBRID INDEX
REAL-TIME
F · 02Connection

The connection layer — your AI tools, plugged into your knowledge.

Anything that speaks MCP (Model Context Protocol) — Claude, ChatGPT, custom agents — retrieves from your Brain in the moment. Your knowledge enters every conversation as context, in the tool you're already using.

Delivers benefit 05
claude · query trace
USER How did we handle the QA gap on the GCSE project last quarter? CLAUDE · via MCP Pulling 3 sources from your Brain… A lesson from project MOR-714 applies. You flagged taxonomy QA at the brief stage… RETRIEVED ● lesson-learned-mor714.md 0.91 ● sop-content-qa-v3.md 0.84 ● retro-2026-Q1.md 0.78 MCP · 1.2s · 3 chunks · trace-id 9f7a
MCP
F · 03Semantic graph

The semantic graph — see what you've built.

A visual, explorable map of your knowledge: dense, interconnected, queryable. The graph answers what have I built? The trace answers what can I do with it?

Delivers benefits 01  ·  03
brain.admin · graph view
EXPLORABLE
F · 04Maintenance

Scheduled maintenance — the operating layer keeps itself current.

Cowork-driven updates run on cadence. New work flows in automatically. SOPs refresh against current reality. Maintenance becomes continuous knowledge enrichment instead of an annual purge.

Delivers benefit 02
cowork · schedule
JOB CADENCE NEXT OK Ingest · briefs/ 15m in 4m SOP refresh daily 02:00 Lessons capture on close trigger Decision log sync hourly 12 min Reindex · changed 5m 2 min Retro digest weekly Fri 16:00 CONTINUOUS ENRICHMENT · 6 ACTIVE JOBS
CADENCE
F · 05OS layer

The operating system around it — Linear, Dropbox, established cadences.

Not just a Brain. A structured way of working — workspace, briefs, lessons learned, project control — that captures knowledge in the shape that compounds.

Delivers benefits 03  ·  04
linear · dropbox · workspace
LINEAR · MOR MOR-913 · Landing page MOR-911 · Q2 SOP refresh MOR-908 · Brain ingest fix MOR-904 · Case study MOR-899 · Lessons retro MOR-892 · Cowork cadence CYCLE 14 · DAY 3/7 42% · ON TRACK DROPBOX · WORKSPACE ▾ /workspace ▾ /briefs mor-913.md mor-911.md ▾ /sops content-qa-v3.md discovery-call.md ▾ /lessons lesson-mor714.md lesson-mor808.md ▸ /decisions ▸ /retros
CADENCES
05Desire

What this looks like in practice.

We built CorpusWire to run MoreResults before we made it available to anyone else. Here's one piece of recent work, with the Brain in the loop.

Case · MOR-904 · GCSE maths taxonomy

A senior team member was authoring a new taxonomy for a GCSE maths content product — three hours of careful, well-scoped work. QA caught a critical gap that would have shipped, because the Brain surfaced a lesson learned three months earlier on a different project that turned out to apply directly.

claude · 21:57:03
01 / 03
QA · TAXONOMY REVIEW Reviewing taxonomy draft for GCSE Maths… 3 sections flagged. Cross-checking Brain… ⚠ GAP DETECTED — Reasoning steps A lesson learned on MOR-714 (3 months ago) applies directly here. You flagged that taxonomies omitting explicit reasoning steps fail downstream QA at the lesson-plan stage. SOURCE ● lesson-mor714.md · §3 retrieved · 0.94 · via Brain MCP
"The Brain catches a gap that would have shipped — pulling context from a lesson learned three months earlier."
brain · 21:57:19
02 / 03
RETRIEVED SOURCE · EXACT lesson-mor714.md § 3 · L 42–58 3. Reasoning steps in taxonomies When authoring content taxonomies for structured subjects (maths, sciences), each leaf node must declare its expected reasoning step. Omission fails downstream QA at the lesson-plan stage. Failure mode observed: Lesson plans generated against a taxonomy lacking reasoning steps produced surface- level questions only. Reshipped Q1 2026. 2026-02-14 · MOR-714 · authored: AT
"Exact document retrieval. Not search results — the actual source."
graph · 16:19:29
03 / 03
"The lesson that closed the gap, retrieved at the moment it was needed."

That's the work we'd otherwise have shipped with a hole in it. This happens every week.

MoreResults · dogfooded since 2025
06Compare

Three alternatives. One real answer.

Alternative · 01

The status quo — no intelligence layer at all.

Folders, scattered drives, AI tools used in isolation. You generate knowledge continuously. Almost none of it accumulates. Every session starts from zero.

TodayCheapest Over timeMost expensive
Alternative · 02

Vendor-owned intelligence layers — "chat with your docs" SaaS.

They own the index, the retrieval, the algorithms, the upgrade path, and increasingly the pricing. Your most valuable institutional asset becomes a hosted feature on someone else's roadmap.

Day oneConvenient Day you leaveIt stays with them
Alternative · 03

DIY engineering build.

You can absolutely build this. You'll also be building it instead of running your business — and maintaining it, and rebuilding it next year when the libraries shift. The reason this isn't already a category isn't that the technology is hard. It's that almost no operator has the time.

CapabilityAchievable CostThe thing you're not running
CorpusWire

Single-tenant, implemented on your stack.

Your database. Your file store. Your domain. Your data. MoreResults builds the system for you and maintains it. The intelligence layer never lives with us in the first place — it's been on your stack the whole time.

The day you stop working with us, you have a working system, not a logout button.

Where it lives
Your infrastructure.
Who maintains it
We do.
Who owns it
You do.
Lock-in
Structural — none.
07Objections

Common questions.

Ordered fit → effort → price → trust → risk → lock-in.

Anchored to document volume and AI usage, not headcount. If you're producing briefs, SOPs, project notes and client correspondence regularly, and your team is already using AI tools daily, the maths works. Five-to-twenty-five-person knowledge-work businesses are the sweet spot.
Most of the work is mapping how your business actually runs, not technical install. The Brain itself indexes a workspace in days. End-to-end implementation typically runs 4–6 weeks before you're in steady-state maintenance.
Bespoke implementations are scoped to fit the business — there isn't a sticker price. We'll know what works for you after a discovery call.
Single-tenant. Everything runs on your infrastructure — your database, your functions, your file store. We never hold your data on our servers. Auth and access are yours to configure.
The engagement runs in phases — scope, install, populate, integrate, train, then maintenance. You see compounding value before implementation completes. If at any phase it isn't delivering, we course-correct or stop.
The system is on your stack. Documentation is yours. You can take it in-house, hand it to another implementer, or run it yourself. The whole point of single-tenant is that you own the layer.

Spreadsheets did this for numbers.
Let's do it for your documents.

Book a discovery call
30-minute call.  No prep needed.  If we're not the right fit, we'll tell you on the call.