12 AI teams. 12 vertical playbooks. One operator console. We deploy the full stack — vault, voice, integrations, employees — tuned to your business. This is the engineering reference for what each piece does and how it’s wired together.
Every BlackMagic deployment ships four things: a Vault tuned to your business, the AI employees that read from it, the integrations they act through, and the operator console you steer them with.
Your single source of truth — voice.md, icp.md, runbooks.md, all the policy that AI employees read from. Audited every action.
Markdown files in team folders. Each employee has a face, a role, a tool stack, and an approval queue. Voice-tuned to your brand.
Slack, Gmail, LinkedIn, Salesforce, Stripe, Linear, GitHub, custom APIs — wired in at deploy time, not bolted on later.
The cockpit you use day-to-day. Home, runs, queues, spend, vault — every team in one room.
Each team is a folder of markdown files with the playbook the AI employees read from. Six are staffed today; six are on the roadmap with named seats and ETAs.
Outbound, SDR, AE copilot, LinkedIn, Researcher, GEO Analyst — every role you’d hire in a Series B sales team, deployed in days, running 24/7.
Bug triage, doc-grade PR drafts, first-pass code review, on-call summarization, release notes — the work that surrounds the work, finally taken off your plate.
AI CSMs run digital success across every customer. They watch usage, ship the right enablement, surface expansion windows, and trigger save plays — humans only on the strategic accounts.
Invoice-in, invoice-out, expense classification, vendor onboarding, monthly close prep, board-pack drafting — the unglamorous 80% of finance, finally on autopilot.
Inbound replies, sourcing pings, scheduled loops, onboarding paperwork, perf-review cycles, comp banding — everything that makes a People team feel like 5 people.
NDAs, MSAs, DPAs, vendor paper, redline rounds, signature flows — the boring work, with audit-grade citations to your playbook.
Content production, ad ops, lifecycle, partner marketing, brand voice. AI marketers ship the routine, brand leads choose the bets.
Pipeline integrity, forecast roll-up, deal-desk approvals, comp calculation, territory ops — all the connective tissue an AE never has time for.
Metric definitions, anomaly detection, ad-hoc analysis, BI maintenance, executive narratives — the whole stack of a real data team in software.
Vendor security questionnaires, evidence collection for SOC 2 / ISO 27001, alert triage, access reviews — the unglamorous work that audits ride on.
Marketing-page wireframes, ad creative, social pulls, UI alt iterations, brand audits — surfaces shipped weekly, not quarterly.
Access provisioning, SSO management, license reclamation, internal helpdesk — the things that quietly tax a company that grew faster than its IT team.
Each playbook is industry-tuned: the right terminology, the right compliance posture, the right outcomes. Every deployment starts from a playbook and is customized from there.
AI employees take the calls, route the trucks, chase the carriers, and rebook a stuck load before the driver finishes their break.
AI employees triage outage reports, dispatch field crews on the right SLA, and answer the customer in their own language before the truck rolls.
AI employees handle irregular ops the moment they hit. Re-accommodate passengers, re-plan crew, draft the gate announcement — before the next flight pushes back.
AI employees do the boring 80%: pull the docs, classify the dispute, score the risk, draft the customer reply. Underwriters spend their day on the 20% that needs judgment.
AI employees plan the merchandising calendar, answer the post-purchase questions, run the returns flow, and surface the SKU you’ll regret stocking out on.
AI employees source the parts, chase the vendors, file the QA paperwork, and surface the supplier risk before the line stops.
AI employees handle the paperwork stack — prior authorizations, payer follow-ups, intake forms, appointment reminders — so clinicians can stay with patients.
AI employees take the FNOL, classify the claim, pull the policy docs, score the risk, and draft the customer letter — before the adjuster opens the file.
AI employees field every inbound, qualify the lead, schedule the tour, draft the lease, and chase the rent — so brokers and PMs do the deals, not the data entry.
AI employees answer the OTA, run the upsell, manage rate parity, and resolve the noisy-neighbor complaint — in seven languages, before the front-desk line forms.
AI employees ship onboarding, watch product signals, surface expansion windows, and reach out before churn — across every account, not just the top 50.
AI employees scope the bid, chase the subs, log the RFIs, file the change orders, and keep the schedule honest — so PMs spend the day on site, not on email.
Context is the on-disk markdown store every agent reads and writes. ICPs, deal histories, objections, tone — one source of truth, versioned, greppable, yours.
Context is just files. companies/acme.md, signals/pipeline-health/, sequences/linkedin-post-signal.md. Open any editor — it just works.
Point at a git repo and every agent edit becomes a commit. Review in your PR tool, merge on approve.
Agents locate files by path and ripgrep, then read with full fidelity. No mystery chunk boundaries, no vector drift.
The Context panel has a full-height editor with ⌘↵ to save. No 320px chat-box clipping, no modal dance.
When an agent proposes a change — new case study, updated ICP — you see the diff before accepting.
Gong transcripts, reply threads, deal post-mortems can be piped into Context automatically, tagged and deduped.
YAML frontmatter (model:, audience:, updated_at:) is parsed by every agent — lets you steer behavior per-file.
Ships with starter files for ICP, brand voice, objection library, case studies, competitor sheets — fill in the blanks.
Long-form research, product docs, battle cards sit alongside operational context — same store, same rules.
Pin exactly which sub-folder an agent may read or write. Reply Guy never touches your deal records.
Lives in ~/Library/Application Support/BlackMagic/context (or your repo). Sync to cloud only if you opt in.
Edit in VS Code, Cursor, Obsidian, vim. Black Magic AI watches the directory and reloads agents as you save.
Because your team already reads and writes markdown in PRs, Notion, Linear. Databases need tooling. Files need nothing — and git gives you history, blame, review, and rollback for free.
Vault was the old name. As of 0.5.19 (April 2026) it is called Context everywhere — same store, clearer word.
Yes. Set context_path to any directory. A git-tracked folder is ideal — every agent edit becomes a reviewable commit.
Tested up to 50k files / 2 GB. Larger stores should be split by concern (ops, content, knowledge) so retrieval stays fast.
Knowledge sits alongside Context — product docs, battle cards, customer research, closed-won post-mortems. Every agent can read it. Every edit is tracked.
Point at a Notion workspace, a Google Drive folder, a website. Knowledge scrapes, converts to markdown, dedupes.
When Outbound says "our enterprise SSO supports SAML and SCIM", it links the exact doc it read — not a vibe.
Tag docs as internal / enablement / customer-facing. Reply Guy never quotes internal roadmap at a prospect.
Operational Context (ICPs, playbooks) + Knowledge (product, research) are one continuous store the agents can traverse.
Fast grep for filename + path, semantic recall for fuzzy questions, always with the raw doc for inspection.
Notion/Drive sources re-sync on a schedule. Stale docs are flagged so no agent quotes a six-month-old price.
PDF, DOCX, PPTX, HTML, Notion export, Google Drive. Converted to markdown, links preserved.
Point at blackmagic.engineering/docs and it pulls the full site, stays in sync, respects sitemap and robots.
When an agent writes a draft, citations are inline. Edit the draft, the citations follow the text.
Every imported doc gets an LLM-generated one-paragraph summary at the top so agents can skim before reading.
A template for closed-won post-mortems (ICP, pain, objection, outcome) that every agent knows how to query.
When multiple drafts need a fact no doc can answer, Knowledge flags the gap and suggests a doc to write.
Context is operational — ICPs, playbooks, brand voice. Knowledge is long-form — docs, research, case studies. Same on-disk store, different folders and different agent permissions.
No. Every doc has an audience tag. Outbound-facing agents are scoped to the customer-facing tag and cannot read internal-only docs.
Yes. Connect Notion, pick the workspaces / pages to sync, and Knowledge keeps a local markdown mirror that re-syncs on a schedule you set.
Edit it in place — or in Notion upstream. The next sync picks up the fix and every agent uses it immediately.
Every vault ships with a library of ready-to-run Skills — brand monitoring, competitor radar, KOL discovery, SEO analysis, CMS publishing, API testing, LinkedIn intel. Each one reads your us/market/* files, fires the right integrations, writes signals/ notes, and sends a notification when done.
Every Skill is a markdown file in playbooks/ with frontmatter (name, agent, inputs, requires) and a prompt body. Version-controlled, diff-able, forkable. No vendor lock.
brand-monitor-apify reads us/company.md. competitor-radar reads us/market/competitors.md. kol-outreach-draft reads us/brand/voice.md. Your context, your output.
Each Skill declares integrations + us_files + cli needed. Pre-flight modal blocks Run until green with one-click fixes — paste a key, fill a file, copy an install command.
Every Skill outputs a dated markdown note in signals/<kind>/<date>.md. Readable, searchable, version-controlled. No dashboard lock-in, no CSV export needed.
Daily Reddit + Twitter/X scan via Apify for brand mentions. Reads keywords from us/company.md. Classifies positive / neutral / negative / question / compare. Writes signals/mentions/<date>.md.
Weekly competitor teardown — pricing / changelog / blog diff against prior week. Reads us/market/competitors.md. Flags material changes to the top of the report.
Finds ICP-matching companies via Apify Google search. Reads us/market/icp.md. Enriches and drafts approval-gated outbound.
Competitor + KOL profile + post diff via Apify. Role changes, engagement-ranked replyable posts. Writes signals/linkedin/<iso-week>.md.
Daily brand + category narrative check. Question-post detection for tool-recommendation threads. High-urgency notify for time-sensitive replies.
Creator-marketing loop: LinkedIn search via Apify → ICP-score against us/market/icp.md → approval-gated DM drafts via draft_create. CSV-tracked end-to-end.
REWRITE / PUSH / GAP analysis from Google Search Console Search Analytics. Daemon signs the service-account JWT for you — no OAuth dance.
Ghost + WordPress. Blog overview and approval-gated draft push. Always creates as draft; you publish via your CMS UI.
Generate + run a JSON test suite via apidog-cli against any REST backend. Covers auth / validation / method / 404 / happy-path. Free npm package, no account.
Building-block skills the Outbound Agent chains. Each one is independently usable — firmographics, ICP scoring, contact enrichment.
brand-mention-scan, competitor-scan, news-scan use only web_search + web_fetch. No Apify needed — run these if you just want the fast, cheap version.
Drop a .md file in playbooks/ with the right frontmatter. Shows up in /skills. Invocable from chat, schedulable via trigger_create. Yours.
Yes — they're markdown files at <vault>/playbooks/. Edit freely. The revision-aware seeder only overwrites your version when the shipped one has a higher revision: number AND you haven't customized. Your edits win.
Yes. Drop <slug>.md in playbooks/. Frontmatter needs kind: skill, name, agent, inputs?, requires?. Body is the prompt an agent follows. Shows up in /skills immediately.
Agents are personas (Researcher, SDR, Outbound, GEO Analyst). Skills are capabilities — a pre-written prompt + tool list that an agent runs. One agent can invoke many skills. The Skills page lets you trigger a one-off invocation for testing.
LLM reasoning goes through our billed proxy. Integration calls (Apify, SES, Google, Ghost, WordPress, GSC) use your own BYOK keys and your own provider bills — we don't touch those.
Twenty-seven first-party integrations out of the box — CRMs, inboxes, data vendors, warehouses. Your existing contracts stay yours. No hidden markup.
Wire your existing Apollo, ZoomInfo, Cognism, Clearbit keys. We route through them at cost. No markup, no resell.
HubSpot, Salesforce, Gmail, Outlook, Slack, Gong, Apollo, Attio, Pipedrive, Stripe, Segment — every major GTM surface.
OAuth where available (Google, HubSpot, Slack), API keys for everything else. Keychain-backed, never logged.
Snowflake, BigQuery, Postgres treated as providers — an agent can SELECT the same way it can call Apollo.
Any Model Context Protocol server plugs in. Tell the agent about a new tool and it uses it on the next run.
Every integration call shows provider, args, status, cost, and latency in the run transcript.
HubSpot, Salesforce, Attio, Pipedrive, Close — bidirectional, with field-level mapping and custom objects.
Gmail, Outlook, Slack, Microsoft Teams, LinkedIn (managed relay or BYOK), Reddit (managed relay), X (BYOK).
Apollo, ZoomInfo, Cognism, Clearbit, PeopleDataLabs (first-party), BuiltWith, Wappalyzer.
Gong, Chorus, Fathom. Transcripts feed replies, signal detection, and closed-lost analysis automatically.
Snowflake, BigQuery, Postgres. Read-only by default; write-enabled with explicit per-table scopes.
OpenAI, Anthropic, Google, plus the Black Magic AI gateway. Pin per agent, BYOK for any provider.
Bring Your Own Key. Paste your Apollo / ZoomInfo / OpenAI API key once; every tool call routes through your account at your contracted rate. We never mark it up.
First-party fallbacks (PeopleDataLabs for LinkedIn enrichment, our own email verifier) kick in. Priced per call, no minimum.
Yes — via MCP (Model Context Protocol). If a system exposes an MCP server, the agents can use it with zero platform work from us.
Every call writes to the run transcript with args, response status, cost, and latency. SOC 2 auditable out of the box.
Every integration is bring-your-own-key. Keys live in a local JSON file and mirror to a plain-text .env in your vault — so scripts, skills, and other tools can all read them naturally. Nothing leaves your Mac except the LLM calls you bill credits for.
22+ integrations, every one BYOK. Paste once in Integrations → Apify (or SES, GSC, Ghost, Unipile, Stripe, GitHub, …). Keys stay in ~/BlackMagic/.bm/integrations.json on your disk, forever.
Every saved integration also writes a plain KEY=value line to <vault>/.env. Your Python / Node / shell scripts just load_dotenv() and read APIFY_API_TOKEN, AWS_ACCESS_KEY_ID, FEISHU_WEBHOOK, SES_FROM, etc.
companies/*.md, contacts/*.md, deals/*.md, signals/*.md, playbooks/*.md, drafts/*.md. Readable in any text editor. Version-controllable with git. Movable to any Mac with rsync.
All tool execution — fetch, scrape, send_email, cms_create_draft, GSC query — runs in a local Node daemon. The only outbound traffic is the target API call + our LLM proxy for billed reasoning.
Stop paying us and the vault stays on your disk. Open it with a text editor. The keys in .env still work with whatever replaces us. Literally no lock-in.
Your vault is git-init'd by default. Diff a contact's history. Revert a bad enrichment. Branch a new ICP to experiment. It's just files.
Canonical store at ~/BlackMagic/.bm/integrations.json. Per-provider { status, connectedAs, connectedAt, credentials }. UI reads + writes, daemon consumes.
Every save regenerates <vault>/.env with predictable names — APIFY_API_TOKEN, AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION, SES_FROM, FEISHU_WEBHOOK, GHOST_ADMIN_API_KEY, GHOST_ADMIN_API_URL, GSC_SERVICE_ACCOUNT_JSON, …
Your credits token lives in .bm/config.toml and is never mirrored to .env. A Skill cannot accidentally use your billing token for unrelated provider calls.
A company is a markdown file. A contact is a markdown file. A run is a markdown file. You can grep, git-log, and rm -rf with confidence.
SES requests use Node's native https module, sidestepping any Electron / Chromium network interference. GSC JWT signing uses Node crypto. No wrapper SDKs that phone home.
Apify charges you directly. AWS SES charges you directly. Unipile charges you directly. We charge you only for credits on the LLM proxy. No 3× markups.
No. Keys live in .bm/integrations.json on your Mac. Integration API calls (Apify → api.apify.com, SES → email.us-east-1.amazonaws.com, GSC → googleapis.com, etc.) go directly from your daemon to the provider. We route only LLM reasoning calls through our proxy — and even those carry your ck_ credits token, not your integration keys.
Yes. Daemon logs every outbound request to ~/Library/Logs/BlackMagic AI/. Plus you can set a proxy and inspect every packet — SES, Apify, Feishu, and all CMS calls are plain HTTPS to the providers' public APIs.
The vault stays on your disk, integrations.json stays on your disk, .env stays on your disk. The desktop daemon stops receiving updates but continues to run. Skills you've customized are yours. Migrate everything to a text editor if you want — it's just .md + .json + .env.
Yes — the vault is designed to be rsync'able / Dropbox-syncable / git-pushable. Keys in integrations.json are machine-local by convention (don't check them into git), but if you want to sync them, that's your call.
.env is the universal interface. Every Python, Node, Go, or shell script in the world knows how to load_dotenv(). Mirroring means any script you write in your vault picks up the same keys you pasted in the UI — zero glue code.
Ask in plain English. Black Magic AI picks the right agent, pulls the right context, calls the right tools, and writes back with receipts — every time.
Mention an agent or just describe the job — the router picks the right one (Outbound, Pipeline Ops, Reply Guy, …) behind the scenes.
Every reply reads from the on-disk Context store — your playbooks, ICPs, past deals — not the open web.
Drop a CSV, a deal record, a LinkedIn URL, a Gong transcript. The chat turns it into structured input for the agent.
Chat writes to HubSpot, fires sequences, runs SQL against your warehouse. Every action is logged with a reversible receipt.
Numbers link back to the CRM record or Context file they came from. One click to verify, one click to edit the source.
Each agent ships with 6 starter chips tuned to its real doctrine — no blank-canvas paralysis.
The default is always the latest frontier model. Pin a specific model per-agent when determinism or cost matters.
Upload spreadsheets, PDFs, decks. The agent writes back markdown, CSV, or JSON you can paste straight into a board.
Dictate your prompt between meetings. Whisper-class transcription with your own vocabulary of buyer names.
Long-horizon tasks (10-minute research, 500-row enrichment) run in the background. The composer unlocks instantly.
⌘K to switch agents, ⌘↵ to send, ⌘/ to cite. Built for people who live in the command line.
When a chat thread is something you want to repeat, one click turns it into a named agent with its own prompt and tools.
No. Chat is grounded in your on-disk Context (playbooks, ICPs, past deals) and has real authenticated tools into your CRM, inbox, and warehouse. ChatGPT has neither.
gpt-5.5 by default, as of April 2026. You can pin a different model per-agent or per-chat — Opus, Sonnet, or your own provider via BYOK.
Yes — every reply shows an expandable trace of the tool calls, their arguments, and their results. Nothing is hidden.
The desktop app keeps Chat History and Context local. Model calls need network, but read-only sessions against cached answers work in airplane mode.
Drafts is the staging area for everything the agents want to send — emails, LinkedIn DMs, Slack nudges. Review, edit, schedule, or flip the switch and let auto-send ship them.
Subject, recipient, body, thread ID — stored on disk. Edit inline, your changes survive regeneration.
Auto-send replies to known customers. Queue first-touch outbound for review. Per-segment rules, not global ones.
The global auto-send toggle is now authoritative. Explicit auto: false from an agent no longer silently overrides it.
Pause the whole queue with one switch. Edit in place. Release individually or in a batch.
Every auto-sent draft has a configurable undo window (default 60s) before it actually leaves your outbox.
See why the draft exists — "LinkedIn post signal", "pricing page visit", "reply needed" — without opening the thread.
Gmail, Outlook, or BYO SMTP. Drafts are real drafts in your sent folder — deliverability is yours.
Through our managed relay or your own account — same review flow, same policy rules.
Send-at-9am-local per prospect. Pause over weekends. Respect your own working-hours policy.
Reply-to-inbound agents can auto-send while outbound agents stay queued — granular controls.
50 drafts look similar? Sweep them with a keyboard shortcut, skim the outliers, ship the rest.
Every draft is written in your brand voice — pulled from context/brand-voice.md and last-10-sent exemplars.
Only if the global toggle is ON. It is OFF by default, and individual agents or audiences can be excluded. Every auto-sent message has an undo window.
Fixed in 0.5.22 (April 2026). The global toggle is now authoritative — explicit per-call auto: false no longer silently overrides your setting.
Yes — select text, ⌘R, describe the change. The rest of the draft is untouched.
Yes — Drafts preserves thread IDs and in-reply-to headers so sent replies thread correctly in the recipient's inbox.
Triggers watch inboxes, webhooks, CRM fields, and external feeds — and fire the right agent the second something happens. Your GTM motion, event-driven.
Point any system at a Trigger URL. The payload becomes structured context for the dispatched agent.
Watch Gmail for replies, bounces, out-of-offices. Each triggers the right follow-up agent with full thread context.
HubSpot or Salesforce: a stage change, new contact, or custom field flip dispatches the matching agent instantly.
LinkedIn post signals, 6sense intent surges, RSS feeds, Reddit mentions — pluggable sources, one dispatch layer.
Cron-style schedules for recurring audits — daily pipeline health, weekly closed-lost rollup — no babysitting.
ICP filters, dedup windows, per-agent rate caps (Reply Guy caps at 5 Reddit / 10 X per day) enforced by the platform.
Declare the payload shape once; incoming events are validated before an agent ever sees them.
Two signals about the same contact in 30 minutes become one agent run, not two duplicate outreaches.
Transient failures retry on an exponential schedule. Dead-letter queue for anything beyond the limit.
Every trigger-started run writes a full transcript to runs/<date>-<agent>/ — grep-able, replayable.
Gmail, HubSpot, Salesforce, Apollo, Gong, Clay, Stripe, Segment, Linear, GitHub, Slack, Zendesk.
A one-off chat that solved a problem can be promoted to a recurring trigger in two clicks.
For revenue workflows, yes. Zapier is great for static flows. Triggers dispatch to agents that handle judgment — edge cases, long tails, weird inputs — without you building a forked graph for each one.
Per-agent rate caps, per-trigger daily caps, and a global kill-switch that pauses every trigger across the workspace in one click.
Yes — the Runs list is chronological (fixed in 0.5.21) and includes both chat-initiated and trigger-initiated runs.
Cron-style schedules fire the same dispatch path — Pipeline Ops daily at 8am, Closed-lost Analysis every Monday, whatever cadence you want.
Black Magic AI ships as a native macOS and Windows desktop. Context lives on your disk. Tool calls happen on your machine. The cloud is optional, never required.
Signed, notarized, auto-updating. Feels like a native app because it is one — not an Electron tab.
Every file the agents read and write lives in a folder on your machine. Cancel us, keep your data.
Tool calls, file reads, git ops run on-device. The cloud only sees what you explicitly route through it.
Browse Context, read chat history, queue drafts offline. The moment wifi returns, queued runs dispatch.
⌘K command palette, ⌘↵ send, ⌘[ history, ⌘\ sidebar. Built for people who live in their keyboard.
App launches in <1s. No spinner, no auth dance, no loading bar — just your workspace where you left it.
Runs native on both Apple Silicon and Intel. Menu bar status, notification center support, system share sheet.
MSI-based installer, auto-update via Squirrel, Start Menu integration, system tray for quick access.
blackmagic on your path — pipe stdin into an agent, tail logs, script your GTM ops from a terminal.
Jamf and Intune deploy packages. Managed config via plist / registry so IT can pre-seed workspaces.
API keys stored in the OS keychain — never in plaintext, never in the cloud unless you ask.
Switch between client workspaces (consultants) or business units (in-house) with a keyboard shortcut.
Yes — the dashboard at app.blackmagic.engineering works in any modern browser. But the desktop app is where the real ergonomics live: offline Context, local tool calls, OS-level shortcuts, and keychain-backed secrets.
~80 MB signed DMG on macOS, ~90 MB MSI on Windows. Auto-update delivers patches in the background.
No. Session is persisted in the OS keychain. Launch the app and you are in.
Point the context_path at a synced folder (Dropbox, iCloud Drive, git repo) and it travels with you. Cloud-side optional sync is on the roadmap.
Every BlackMagic deployment is tuned to one customer. We read your playbooks, wire your integrations, voice-train your employees, and stand up the operator console — production-ready in days, not quarters.
