The pattern: cloud AI means your books, clients & processes leave the building. MAJIC runs on your own GPU — nothing leaves.Live🧠
Business Intelligence (Local LLM)
Private, on-prem intelligence & optimization on your own local LLM — your data never leaves your walls.
The problem it solves
Most businesses can't use AI on their real numbers — it would mean shipping financials and client data to someone else's cloud. MAJIC answers from your own private SQL knowledge base, on hardware you own, so it can reason about your actual operation without the data ever leaving.
What we're working on next
Richer optimization & ROI insight — "if your IT budget is $X across Y employees, here's the estimated savings range."
The pattern: ten AI tools, ten logins, ten bills, none of them talking to each other. One front door instead.Live✨
majic.ai Core
The MAJIC platform: chat, agents, automation, and the capabilities that tie every module together.
The problem it solves
Teams end up juggling a pile of disconnected AI tools that don't share context. majic.ai Core is the single front door — one chat, one agent layer, one automation engine — that every other module plugs into, so the AI keeps context across your whole business.
What we're working on next
Consolidating the full stack under appmajic.ai — unified login, app, API, installer, and the module marketplace in one place.
The pattern: a 200-page plan set takes an estimator days to count drops and write a bid. MAJIC does the read in minutes.Live📐
Proposal Generator
Auto-extract plans and generate bids & proposals (Division 27/28 low-voltage) in minutes, not days.
The problem it solves
Bidding from plans is slow, manual, and error-prone — someone hand-counts every drop, device, and run across hundreds of pages. MAJIC ingests the plans zip, flattens it page-by-page, runs a multi-phase extraction, synthesizes the scope, and generates a finished, compliance-checked proposal PDF — turning days of take-off into minutes.
What we're working on next
Tighter labor-plan & alternates gating, richer sample-output galleries, and licensing the engine to other trades.
The pattern: a small business can't afford a full IT team, so problems wait until something breaks. MAJIC watches and fixes 24/7.Live🛡️
Managed IT / MSP
NOC dashboard, agent fleet, AD/DNS/IIS roles, and auto-remediation — your always-on Tier-1/2 IT department.
The problem it solves
Hiring a Tier-1/2 IT team is expensive; without one, issues fester until something breaks. A tiny agent on each machine reports to a central dashboard and runs fixes itself — a command dispatches and the target runs it within seconds — so patching, monitoring, and remediation happen automatically across every PC and server.
What we're working on next
Deeper self-healing playbooks and a one-click remote-access dashboard shared with the Pool Party opt-in path.
The pattern: cloud image/video credits get pricey fast. Spread the work across machines you already own.Live🎬
Media Generation Pool
Distributed image & video generation node pool for on-demand creative output.
The problem it solves
Per-image and per-second cloud media pricing adds up fast. MAJIC pools GPU nodes you already own — they enroll to a central registry and the orchestrator routes each job to a free node — so creative output scales on your own hardware instead of a metered cloud bill.
What we're working on next
Splitting into specialized pools — image variations and long-form video — and growing the node fleet via Pool Party.
The pattern: picking the right image means trying many. Generate a whole batch at once instead of one-at-a-time.Live🖼️
Pooled Image Variations
Generate many image variations in parallel across distributed media nodes — fast, on-demand creative iteration.
The problem it solves
Finding the right visual usually means generating one option, waiting, tweaking, and repeating. By fanning a single prompt across many pooled nodes at once, you get a full spread of variations in the time one would normally take — so you pick instead of wait.
What we're working on next
Smarter node load-balancing and style-locking so variation batches stay on-brand across every node.
The pattern: long video is the most expensive thing to render in the cloud. Split it across your own nodes like a film farm.Live🎞️
Pooled Video
Render long-form video across distributed nodes — split, generate, and stitch big jobs the cloud charges a fortune for.
The problem it solves
Long-form video is where cloud generation gets brutally expensive. MAJIC splits a big render into segments, generates them in parallel across pooled nodes — like a render farm — then stitches the result, so length stops being a cost wall.
What we're working on next
Longer continuous sequences, keyframe sync across nodes, and automatic reassembly of multi-node renders.
The pattern: your PC sits idle most of the day. Lend it to the pool and earn free IT management in return.Live🤝
Pool Party Stack
Opt your PC in as an LLM node in the MAJIC pools — in exchange you get automatic PC management, updates, and a remote-access dashboard.
The problem it solves
Most machines are idle the majority of the day, and small shops still need their PCs managed. Opt a machine into the pool and its spare capacity helps run the MAJIC AI pools — in exchange you get automatic PC management, updates, and a remote-access dashboard for free. A fair trade of idle cycles for managed IT.
What we're working on next
One-click remote node installer, fair-use contribution credits, and a self-service opt-in/opt-out dashboard.
The pattern: the answer is buried in a giant PDF no one wants to read. Turn the pile into something you can query.Live🔎
Holmies Parse Model
Our multi-phase extractor — generalized as a plugin. Intakes large files and varied document types, and produces organized, referenceable extractions.
The problem it solves
Critical detail hides inside huge, messy documents that don't fit in an AI's context window. The same multi-phase extractor that reads construction plans, generalized: it ingests large files of many types and produces organized, referenceable extractions — isolated per job — so any system can ask precise questions and get sourced answers.
What we're working on next
More document types out of the box and a cleaner plugin API so any app can drop in structured extraction.
The pattern: "file too large / too many pages" — the upload your favorite AI keeps rejecting. SherLockItIn slips it in.Live🕵️
SherLockItIn
A connector for the big chat models (Perplexity, ChatGPT, Claude, Cursor & more) that enables inline upload of large files — flattens them and saves page-by-page next to the originals so any AI can process them.
The problem it solves
The big chat models choke on large or multi-page files. SherLockItIn adds a connector that flattens an upload and saves it page-by-page right next to the original, so Perplexity, ChatGPT, Claude, Cursor and others can actually read it — and it drops a README that tells any AI what's what.
What we're working on next
Auto-dropping a README that explains what's what to any AI, plus more host integrations and bigger file limits.
The pattern: one model trying to do everything does it all mediocrely. A dispatcher sends each job to the model built for it.Coming Soon🧩
SIYL LLM
Stay-In-Your-Lane LLM — the orchestrator that routes every call across the AI stack and keeps each model focused on the task it does best.
The problem it solves
Using one giant model for everything is slow and uneven. SIYL is the dispatcher — like a shop foreman — that classifies each request and routes it to the right model: a fast one for quick chat, a deep one for hard reasoning, a vision one for images. Every AI stays in its lane and does the one thing it's best at.
What we're working on next
Hardening the classifier, single-entry routing for all AI calls, and per-task lane enforcement so no model drifts off its strength.
The pattern: chat usage spikes are unpredictable. Borrow capacity from the pool instead of overpaying for cloud headroom.Coming Soon💬
Pooled Chat
A distributed node pool for chat requests — the same Pool Party model applied to live conversation, for scale without the cloud bill.
The problem it solves
Chat demand is spiky — quiet most of the time, then a rush. Rather than pay cloud rates for peak headroom you rarely use, Pooled Chat spreads live conversation across contributed nodes, so capacity flexes with demand without the metered bill.
What we're working on next
Routing chat across contributed nodes with low latency and graceful fallback when a node drops.
The pattern: starting a business shouldn't require an IT degree. Hand it a PC — or just an idea — and it sets the rest up.Coming Soon🧰
IHateIT Suite
Automatic build-out of a small business's basic IT. Hand it a PC or server, or let it walk a brand-new business through Cloudflare signup, buying a domain, defining their offering, and building a website — with a private login side to see their numbers and chat with their business advisor.
The problem it solves
New and small businesses face an IT wall before they ever open: domains, hosting, a website, a place to see their numbers. IHateIT either stands up basic IT on a PC/server you hand it, or walks a brand-new business through it end-to-end — Cloudflare signup, buying a domain, defining the offering, building the site — with a private login side for their numbers and a built-in business-advisor chat once it's live.
What we're working on next
Guided new-business onboarding (domain → site → private portal) and a clean handoff into the business-advisor chat once setup is done.
The pattern: not every business has servers on-site. Same managed-IT coverage, built for the cloud.Coming Soon☁️
BlueSky Cloud IT
Cloud-hosted managed IT & MSP for businesses running on cloud infrastructure.
The problem it solves
The MSP module is built for on-prem fleets, but plenty of businesses run entirely in the cloud. BlueSky brings the same managed-IT coverage — monitoring, remediation, role management — to cloud-native infrastructure for shops without a server closet.
What we're working on next
Standing up the cloud control plane and porting the on-prem MSP playbooks to cloud-native targets.
The pattern: fees and timing quietly eat returns. Model them before risking a dollar.Coming Soon📈
TraderMikes
AI-driven investing — learning stock & crypto fees and patterns.
The problem it solves
Hidden fees and bad timing erode investing returns more than most people realize. TraderMikes is our R&D effort to learn the fee structures and recurring patterns across stock and crypto markets first — understanding the math before any live signal ever goes out.
What we're working on next
Modeling fee structures and recurring patterns across markets before any live signals go out.
The pattern: electrical estimators count fixtures and runs by hand too. Same plan-reading engine, electrical scope.Coming Soon⚡
Electrical
Electrical plan take-offs and quotes via the same automated proposal process.
The problem it solves
Electrical contractors face the same slow, manual take-off as low-voltage — counting fixtures, circuits, and runs across big plan sets. Electrical applies the proven Proposal Generator engine to electrical scope, shaped by field input from our electrical partners.
What we're working on next
Finishing the electrical-plan extraction pass and quote logic, shaped by field input from our electrical partners.