Seed Stage · Operating System for your AI

One engineer,
the output of an
entire AI team.

Vodou is a local-first AI operating system for technical power users running more projects than there are hours in the day. It remembers your context, routes each task to the right model, skill, or tool, and runs them in parallel — all on your machine.

Stage
Pre-Seed
Current Phase
Alpha Testing
Focus
Technical Power Users
Architecture
macOS · Local-first
▸ Windows & Linux builds in testing
Start here · 60-second overview
Meet Vodou.

The fastest way to understand what we have built — the problem, the product, and the outcome, in a minute.

Let’s accelerate what the world’s boldest AI builders can create.
01 / Target User

The technical power user is the wedge. Not the whole map.

Vodou is built first for one person: the engineer, AI developer, or technical consultant running multiple complex projects across multiple models — and losing hours to the seams between them. They’re the fastest to adopt, the cheapest to reach, and the loudest when something works. They’re also, eventually, the people inside the engineering organizations we intend to sell to next.

AI engineers & developers Technical founders Independent consultants Agency & studio leads Multi-project operators AI power users
Persistent memory

Nothing gets re‑explained.

Every session opens where the last one closed. Project context, decisions, constraints and preferences persist across models and across days — so the single largest recurring tax on AI-assisted work simply stops being charged.

BrainLoader

You stop being the router.

The BrainLoader reads the intent behind a request and dispatches each part to the right resource — a model, a skill from the 141-skill library, an MCP tool, a scheduled automation. You describe the outcome. It decides the path.

Parallel orchestration

Work happens at once, not in line.

Every dispatched resource runs simultaneously, gets quality-scored at the pass, and comes back as one synthesized answer. Four projects move at the same time because you are no longer the bottleneck between them.

The outcome we sell

The net effect is capacity. Vodou does not help someone work harder. It lets one person carry more work at the same time, because the software holds the context and does the coordinating that person used to do by hand. For a consultant, that is room for another client. For an engineer, it is finishing in a week what used to take three. Our users are not beginners who need help — they are skilled people who have run out of hours. They feel the difference within days, which is why $40–$100 a month is an easy yes, and hard to give up once it is part of how they work.

And this is the wedge, not the destination

Every pain the individual feels — lost context, fragmented tooling, knowledge trapped in one person’s head — multiplies inside an organization once roles, handoffs and turnover enter the picture. Shared memory, team knowledge bases, governance and guardrails are what turn this from a personal tool into operational infrastructure. That is the enterprise motion, and it is what this round funds. The individual product is how we earn the right to sell it.

02 / The Problem

AI today is powerful, but profoundly fragmented.

One problem, felt twice. The technical power user hits it every day. Inside an engineering organization the same failure multiplies roughly threefold — once roles, handoffs and turnover are added to it.

Primary · Technical Power Users & Engineers
The tools are smart. The system is dumb.
[ 01 ]
Context dies on every session.
The smartest models still wake up with amnesia. Every morning starts by re-explaining the project, the decisions, and the constraints that were already settled yesterday. It is the single largest recurring tax on AI-assisted work.
[ 02 ]
The human is the router.
Six tools, none of which know the others exist. The person decides what goes where, carries the output between them by hand, and holds the whole plan in their head. That coordination work is unpaid, invisible, and constant.
[ 03 ]
Everything runs one at a time.
Tabs, chats, copy-paste, manual handoffs. Work that could happen simultaneously queues up behind one person’s attention instead — so capacity is capped by hours in the day, not by capability.
The same problem, multiplied · Engineering Organizations
Now give that problem an org chart.
[ 04 ]
Now everyone routes separately.
Every engineer builds their own private setup with their own tools and their own prompts. Departments deploy independently. No governance, no coordination, and no way to see what AI is actually doing across the business.
[ 05 ]
Institutional knowledge keeps walking out the door.
Process lives in people’s heads, not in systems. Context that never left one engineer’s laptop leaves the company with them, and turnover resets the operation. AI is bolted on, not built in.
[ 06 ]
The same work gets solved five times.
What one engineer figured out last month, another rediscovers this month. Nothing compounds, because nothing is shared — and onboarding a new hire means rebuilding all of it from scratch.
03 / The Market

A generational infrastructure opportunity.

Every organization is buying AI. Almost none are coordinating it. The orchestration layer is the next platform shift — and it's wide open.

TAM · Total Addressable
$1.3T
by 2032
Global enterprise AI & automation spend.

Every knowledge-work organization on Earth eventually runs on an orchestration layer. This is the long-horizon prize.

SAM · Serviceable Addressable
$180B
by 2028
AI orchestration & agent infrastructure.

Mid-market and enterprise buyers actively budgeting for AI workflow, memory, and multi-agent execution — Vodou's direct lane.

SOM · Reachable Initial Market
$300M
platform-managed spend · 5 yrs
AI workflow spend managed through Vodou.

The cumulative AI workflow spend we expect to operate on top of over five years. Vodou's revenue comes from a take-rate on this managed spend, not the figure itself.

Why now.  Frontier models are commoditizing fast. The durable value is moving up the stack — into memory, orchestration, and execution. The infrastructure layer between intelligence and outcomes is being defined right now, and there is no incumbent.
04 / Vodou OS
VODOU OS Phase one · built for the technical power user

Control your AI.

The three problems above, solved in one runtime — running locally, on your machine.

Vodou OS is the infrastructure and execution layer for agentic AI. Memory ends the re-explaining. The BrainLoader takes over the routing. Parallel execution lifts the cap on how much one person can move at once. Models, MCP tools, workflows, skills and scheduled jobs all run through a single centralized runtime — so instead of the user tying six disconnected apps together by hand, the system does it, and gets more valuable the longer they use it.

  • Persistent memory — context that compounds across sessions, projects, and tools. Nothing gets re-explained.
  • BrainLoader routing — intent is read once and dispatched to the right model, skill, tool, or automation. The user stops being the router.
  • Parallel execution — multiple models, tools, and jobs running concurrently through one runtime. Work stops queueing behind one person.
  • Universal connectivity — MCP-native, with a 141-skill library, scripts, and tool orchestration built in.
  • Local-first architecture — your data, your machine, your control.
  • Deterministic workflows — reliable, repeatable execution beyond one-off prompts.
vodou.os · orchestration
INPUT "Refactor the auth module and write tests"
ROUTE BrainLoader → memory · skills · 3 models ~120ms
EXEC parallel: code-gen × test-gen × review 25-50x
MEM FTS5 + vector store · daily logs persisted
DELIVER files · slack · pages · artifacts multi-channel
DONE context retained · workflow saved +1 skill
05 / Orchestration, Explained

First, the plain-English version: a kitchen.

Before the technical pipeline, here's the whole idea in one interactive picture. Press "Fire the order" and watch a single request move through the kitchen — then read the Rosetta table to see exactly what each step means in AI. This is the same explainer that lives on vodou.ai. It's live — click around.

06 / How It Works

From plain English to executed answer.

Every request flows through one pipeline. Intent is parsed, memory is loaded, the right tools are routed and called, then a single model synthesizes the answer.

⚡
Vodou's secret sauce
The BrainLoader is proprietary to Vodou
Every other platform makes you decide which AI tool to use. The BrainLoader does that for you — it reads the intent behind your request, pulls in your stored memory as context, and decides in milliseconds whether to run a skill, route to a tool, or call an LLM. That decision engine is Vodou's IP. No one else has it.
YOU
You
a plain-English request
↓
HOW IT REACHES VODOU
Inputs
Web · IDE · Slack · Telegram · Discord
Automations
Scheduled tasks · triggers · hooks · cron
↓
PROPRIETARY · VODOU IP
BrainLoader
reads intent · loads memory · routes to the right tool · our secret sauce
ROUTING ENGINE → SEQUENTIAL · BEST PATH WINS
Intent Router
maps request to the right tool
Skills Engine
runs a pre-built skill · fast · no AI needed
Apps / MCP Servers
3rd-party tools & APIs called on demand
CONTEXT ASSEMBLY
LLM Context
your memory + tool results pre-injected as rich intelligence — ready for reasoning
↓
LLM Reasoning
best AI model synthesizes the final answer
↓
Your Answer
file · report · HTML · Slack message · code · widgets
ALWAYS ON: Memory indexingScheduler (cron)HooksFile watcherHook processing
07 / Vodou Enterprise
vodou.enterprise · org graph
VODOU CRM ERP DOCS OPS CHAT DATA
VODOU ENTERPRISE For mid-market & large organizations

Operationalize AI
across the whole org.

A custom AI orchestration and operationalization platform built on the Vodou OS backbone.

Most organizations adopt AI in fragmented, uncoordinated ways. Departments operate independently, workflows stay disconnected, institutional knowledge gets trapped. Vodou Enterprise creates one coordinated operational intelligence and execution layer across the business — connecting workflows, internal tools, automation, reporting, and organizational memory.

  • Operationalize AI — embed it into the workflows your business actually runs on.
  • Preserve institutional memory — knowledge that survives turnover, not buried in people's heads.
  • Centralized governance — guardrails, permissions, and private/local deployment options.
  • Custom execution systems — built to how your organization actually operates.
  • Phased engagement — discovery, design, pilot, deployment, and scale across the org.
08 / The Product

It's not a deck. It's real software.

Vodou is already running in alpha — 36,000+ memory chunks, 141 active skills, 29 live MCP servers and ten messaging channels, all on the user’s own machine. Every screen below is the actual product, captured from a running build.

vodou · brain · constellation
Your AI, Remembered.
36,181 memories
Compounding Memory
Your AI, Remembered.
Vodou automatically remembers everything you do with AI, lays those memories out like a map, and lets you share just the parts you want with other people.
vodou · brain · vaults
Own Your Own Data
Own Your Own Data
Own Your Own Data
Every memory carries its source and a trust weight — yours, auto-captured, or imported. Share vaults hand a named slice to someone else without opening the whole store.
vodou · bridge · chrome extension
Vodou Remembers Everywhere
Everywhere You Work
Vodou Remembers Everywhere
Vodou quietly saves what you do with AI — in your browser, your coding tools, or your other apps — all into one place, and it figures out which memories to trust most.
vodou · chat
From Words to Answers
Natural Language In
From Words to Answers
Type what you want in plain English. Vodou figures out what you meant, remembers what it knows, picks the right tools, and puts together one clear answer.
vodou · kanban board
A Board That Works Itself
Autonomous Workers
A Board That Works Itself
Drop tasks onto the kanban board, and Vodou’s agents pick them up and start doing the work for you, right when you need them to.
vodou · messaging
Talk to Vodou Anywhere
10 channels
Universal Channels
Talk to Vodou Anywhere
Receive and reply on Slack, Telegram, Discord, Teams, WhatsApp, iMessage, Google Chat, Signal, Voice and the Web — you control the setup and who’s allowed in on each one.
vodou · apps
Apps, Integrations & Tools
MCP-Native
Apps, Integrations & Tools
Connect apps, accounts, and other integrations such as MCP servers with just a few clicks.
vodou · skills & tools
Specialists on Call
141 active skills
Composable Skills
Specialists on Call
Ready-made expert agents for engineering, design, research, and ops — plus tools and automations to chain into workflows, all orchestrated for you.
vodou · settings · memory tuning
Tune Your Memory
Governed Capture
Tune Your Memory
One screen shows how much Vodou remembers and where it’s coming from — flip any source on or off to control what gets saved.
vodou · system
Under the Hood
Local Runtime
Under the Hood
One dashboard shows if everything’s running right, how many memories you have, and whether you’re up to date — with a button to fix or roll back updates.
Live walkthrough for investors

Screenshots only go so far. Come watch it run.

Vodou is working software, not a roadmap — and the fastest way to understand it is to watch a request get decomposed, routed across models, skills and tools, executed in parallel, and reassembled in real time. We run 45-minute live sessions for investors and their technical diligence partners: a walkthrough of the running product, the BrainLoader and memory architecture under the hood, and open Q&A with the founding team. Bring your own use case and we will run it live.

Request a demo → Usually scheduled within 48 hours
09 / Design Partners

The people already running it daily.

Vodou has been running with a small group of design partners — operators, builders and technical leads using it against real workloads, not demos. They shape what gets built, and their feedback is what set the beta feature lock.

“

The biggest benefit of Vodou is capacity. I can manage more complex work at once without spending so much time coordinating between different tools.

AR
Adam R.
Fractional COO
“

Vodou helps me pick up where I left off without constantly re-explaining the context. I’m able to stay in motion and move my work forward much faster.

JB
Jon B.
Group Creative Director · Financial Services
“

Vodou lets me focus on the outcome instead of figuring out which model, tool, or workflow to use. It removes a lot of the manual coordination from AI-assisted work.

CS
Chris S.
Product Designer · Music Tech & Creator Tools
“

Instead of moving through everything one task at a time, Vodou helps me advance multiple projects in parallel. I’m getting more leverage from the same amount of time.

BK
Bridget K.
VP Partner Development · Technology Broker
10 / Competition

Everyone owns one layer. We own the seam between them.

The field has split into three camps: agent runtimes that execute, workspaces that aggregate models, and memory add-ons that remember. Each is strong in its lane and blind to the other two. Vodou is the only one that runs all three on your own machine, under one governed pipeline.

Cowork is Anthropic's agent, on Anthropic's models. OpenClaw is a self-hosted loop with 60+ CVEs. Hermes is a learning loop that ships fast. Poe rents you every model and remembers almost nothing. MemoryPlugin and ByteRover sell the memory the runtimes forgot.
Vodou is the layer that makes those four problems one product — locally.

↔  Scroll the table horizontally to compare all eight

Horizontal layer Agent runtimes Multi-model workspaces Memory add-ons
Capability Vodou v0.6.21 · private alpha Claude Cowork Anthropic · Opus 5 default OpenClaw 2026.6.8 stable · ~379K★ Hermes Agent v0.20.0 · Aug 3 2026 Poe Quora · $20.99/mo Pro AnythingLLM MIT · desktop + docker MemoryPlugin $79–149/yr · 21+ tools ByteRover free / $14.90 · IDE-side
Deterministic routingbefore the LLM ✓BrainLoader — 3,541 intent mappings resolve skills, tools and scripts before inference ✗Claude-native agent loop decides ~Skill match, then the model decides ~Agent loop over self-distilled skills ✗You pick the bot ~Rule-based model routing only ✗Not a runtime ✗Not a runtime
Local-first executionincl. inference ✓Runtime and memory 100% local; bundled llama.cpp + LM Studio for local inference ~Agent loop and file access local; shell and code run in Anthropic's VM, inference cloud ~Self-hosted gateway, cloud LLMs ~Self-hosted; Daytona/Modal serverless path ✗Fully cloud ✓Fully local with Ollama backend ~Hosted by default; local MCP server offered ✓Local by default, cloud sync optional
Compounding memorygoverned, not a log ✓37.8K chunks — FTS5 + vector + reranker, contradiction and dedup passes, health-gated retrieval ~Memory + "Dreaming" consolidation — cloud-held, not inspectable ~Plaintext markdown diaries, unencrypted at rest ~FTS5 recall + Honcho user modeling (off by default) ~Off by default, updates once a day, absent in group chat ~Per-workspace RAG; no cross-session user model ✓Buckets, edits, history import — vendor-held ✓Hierarchical store, 92.2% retrieval accuracy claimed
Memory that follows youacross other AIs ✓Bridge extension captures 22 chat surfaces and injects back into 18 verified — plus Cursor and Claude Code ✗Anthropic surfaces only ✗Its own agent only ~8 pluggable memory providers — still only inside Hermes ✗Poe only ✗Its own workspaces only ✓21+ AI tools — the closest direct rival ~IDE agents only (Cursor, Copilot, Claude Code, Cline)
MCPclient and host ✓26 servers as client, and a host: any local MCP client attaches with its own token, profile and vault ✓Client — local and remote connectors ✓Client ✓Client ~No first-party MCP; community servers wrap the API ✓Client, and serves as a server to Claude Desktop ✓Hosted remote MCP (OAuth/PKCE) + local server ✓MCP into any AI IDE
Parallel tool execution ✓Connection pooling, 25–50× over serial dispatch ~Parallel sub-agents on Opus 5 ~Serial by default, sub-agents available ~Agent loop plus agent-to-agent (A2A v1.0) ~Side-by-side model compare, not tool orchestration ~Sequential agent runs ✗— ✗—
Composable skills ✓144 skills, user-authored, no registry gatekeeper ~Skills and plugins, curated by Anthropic ✓ClawHub — 13.7K community skills ✓Self-distilled skills + plugin SDK ~Custom prompt bots, no tool runtime ~Agent builder over MCP tools ✗— ✗—
Multi-channel delivery ✓10 channels — Slack, Teams, Telegram, Discord, WhatsApp, Signal, iMessage, Google Chat, web, voice ✗Desktop, web and mobile app only ✓25+ platforms through the gateway ✓20+ channels, streaming voice in v0.20 ✗Poe app only ✗App only ✗Browser extension only ✗IDE only
Model freedomBYOK and local ✓OpenAI-compatible API, any provider, local models first-class — BYOK never metered ✗Anthropic models only ~Any provider you configure ~Multiple providers supported ✓Every major model on one subscription — but you choose per chat, and only theirs ✓Any provider, with dynamic routing rules ✗— ✗—
Governanceaudit, scope, revoke ✓Zero mandatory cloud. Per-client identity, egress profiles enforced pre-dispatch, salted audit log, rate limits, surgical revoke ✗Cowork activity excluded from Audit Logs, Compliance API and Data Exports — every tier, Enterprise included ✗60+ CVEs, ~30K exposed instances, a poisoned skill marketplace ~Self-hostable; secrets via 1Password / Bitwarden ✗Quora-held, no tenant controls ~Self-hosted, but no governance layer of its own ~Encrypted in transit and at rest — vendor-held ~Local by default, cloud sync opt-in
Unified pipelineone product, not four ✓Routing + memory + tools + delivery in a single governed path ✗Agent only ✗Agent + skills, no unified pipeline ~Agent + learning loop, memory pluggable not governed ✗Model access only ✗RAG workspace only ✗Memory only ✗Memory only
✓shipped and verified ~partial, conditional, or off by default ✗absent or out of scope
The takeaway.  Buy Cowork and you get Anthropic's models with no audit trail. Buy Poe and you get every model with no memory. Buy MemoryPlugin and you get memory with no runtime. Self-host OpenClaw and you inherit its CVEs. Vodou is the only one where routing, compounding memory, tool orchestration and delivery are the same governed system — and the only one that keeps all four on hardware you own.

Vodou column verified against the codebase 2026-08-09 — v0.6.21, 144 skills, 26 MCP servers, 3,541 intent mappings, 37,846 memory chunks, 10 channels, 22 capture surfaces (18 save-verified).
Competitor columns verified from primary and press sources, 2026-08-09. Hermes v0.20.0 (2026-08-03); Cowork on Opus 5 (2026-07-24), compliance exclusion documented May 2026; OpenClaw stable 2026.6.8.
Soft data, flagged: OpenClaw star counts and beta tags conflict across sources (~379K cited here); Nous Research's $75M round at $1.5B is reported "in advanced talks," not closed. Also in field, not charted: mem0, Supermemory, Honcho, Msty, Jan.

11 / Architecture

One product. Two phases.

These are not two bets running in parallel. They are two stages of one motion. Vodou OS wins the individual technical user and builds the orchestration infrastructure underneath them; Vodou Enterprise takes that same runtime into the organizations those users already work inside. The first earns the second — bottom-up adoption creates the installed base, the reference customers, and the operational proof that a top-down enterprise sale requires.

/ PHASE ONE · NOW

Vodou OS wins the individual.

Local-first runtime, memory architecture, parallel orchestration, MCP-native tool layer. Sold direct to technical power users at $10–$100 per seat per month. High volume, low friction, no procurement cycle — and every seat is a person embedded inside a company we intend to sell to.

/ PHASE TWO · NEXT

Vodou Enterprise scales it.

Shared memory, team knowledge bases, governance and guardrails on top of the same runtime — deployed inside organizations to connect fragmented systems and preserve institutional knowledge. Six-figure engagements, sold to the CTO. Paid assessments begin early and fund the build.

12 / Financials

Two scenarios. One cost base.

Both cases below share the same costs, the same hiring plan, and the same team. The only thing that changes is how fast we grow. Nothing here is a guess — our pricing tiers set the average revenue per user, the trial funnel and churn rate set the subscriber count, and inference, cloud, payment and support costs are calculated per user. Margin is the result, not an assumption. The base case is the plan we are funding. The upside case is what the same business does if adoption and retention come in stronger.

Base case · operating plan
$2.83M
FY 2027 total revenue

10% trial conversion, 6% monthly churn, $38.50 blended ARPU. Exits December at $434K net subscription MRR — a $5.2M ARR run-rate entering 2028. This is the plan we're funding.

Ending paid seats12,408
Gross margin48.3%
Operating result($938K)
Q1 → Q4 quarterly burn$356K → $44K
December operating result+$4.5K
Upside case · same cost base
$8.09M
FY 2027 total revenue

20% trial conversion, 4% monthly churn, $52 blended ARPU. Crosses into monthly operating profit in April and finishes December at a $15.4M annualized subscription run-rate — self-funding from Q2 forward.

Ending paid seats27,000
Gross margin61.6%
Operating result+$2.33M
Net cash flow pre-financing+$2.30M
December operating result+$695K
Monthly total revenue · Jan → Dec 2027 Base Upside December exit
Jan ’27Jun ’27Dec ’27
Blended ARPU / mo
$38.50– $52
Derived from plan mix across five tiers — not a flat assumption.
Gross margin
48.3– 61.6%
After inference, cloud, payment processing, support and delivery.
Paid-media CAC
$10.56– $14.79
Ad spend per new paid seat. Excludes content, events and GTM payroll.
LTV / loaded GTM CAC
8.2– 30.9x
Directional. Uses full sales & marketing payroll plus non-payroll GTM.
Monthly seat churn
6– 4%
47.6% to 61.3% annualized retention. Our hardest number to prove.
Trial → paid conversion
10– 20%
60-day trial, no credit card. Trial inference is costed as COGS.
Subscription share
91– 93%
Recurring software, not services. Enterprise is additive, not the engine.
Inference cost / seat
$4.80– $10.43
Weighted across included token allowances at modeled utilization.
Where the ARPU comes from — pricing ladder & plan mix Upside-case mix shown
Plan
Price / mo
Included tokens
Share of seats
BYOK
$10
Bring your own keys
10%
Starter
$20
2M
15%
Standard
$40
5M
25%
Pro
$60
10M
30%
Power
$100
25M
20%
Weighted blended ARPU  $52.00 Inference margin at full token use  61–84% by tier Overage revenue modeled at  $0

Enterprise is the second engine — deliberately staged.

Vodou Enterprise revenue is built deal-by-deal off the service framework, weighted to the back half of the year once the OS is proven in production. We model it conservatively and treat it as additive to the subscription business, never as a substitute for it.

Operational AI assessment
$30K × 3
Entry engagement. Maps fragmented systems and scopes the operating layer.
Targeted pilot
$125K × 2
Production deployment against a single high-value workflow.
Operating-layer rollout
$210K × 1
Org-wide implementation. Converts to ongoing optimization and support.
What this is, and what it isn’t.  These figures come from Vodou’s bottom-up 2027 forecast workbook — thirteen linked schedules covering pricing and mix, the subscriber build, enterprise deal staging, headcount, COGS, unit economics, cash runway and sensitivity. Inference is priced against published per-million-token rates; payment processing against published card rates; support headcount is formula-driven from modeled ticket volume. Overage revenue is modeled at zero. Enterprise revenue appears early in the model by design — paid assessments are how we learn what the enterprise product must be, and they are scoped so that discovery is funded rather than speculative. The model runs through December 2027 only — we are not projecting 2028 until the acquisition funnel has live operating data behind it. Opening cash is $50K; the $2.0M raise carries the base plan through the year with roughly $1.09M remaining, and the upside case never draws below its opening balance. Full workbook, monthly detail and sensitivity tables available under NDA.
13 / The Ask

A staged round, built for capital efficiency.

We're structuring the raise in two stages so investors can right-size their entry. A lean pre-seed unlocks immediate execution; the full seed delivers 14–18 months of runway to revenue, public launch, and Series A readiness.

▸ Immediate · Pre-Seed
$500Ktarget

Bridge to soft launch & enterprise pilots.

A focused tranche that funds alpha stabilization, the push to beta, enterprise pilot outreach, and Vodou OS soft launch. Designed for angels and pre-seed funds with smaller check thresholds.

Open now $25K–$100K checks SAFE ~4–6 mo runway
▸ All-in · Seed
$1.8–2.1Mtarget

14–18 months to revenue & Series A.

Full seed round funding engineering scale, GTM, infrastructure, and founder-led enterprise sales. Pre-seed converts into this round. Designed for seed funds and strategic angels with conviction on AI infrastructure.

Lead invited $100K–$500K checks SAFE 14–18 mo runway

Allocation at full raise

45%
Engineering & Product
Hire 2–4 engineers · beta to production · Windows + Linux expansion · orchestration engine, QA, DevOps
$850K – $900K
20%
Go-To-Market & Community
Developer community + content engine · launch marketing · product-led growth on GitHub and dev channels
$350K – $400K
15%
Infrastructure & Operations
Cloud + compute scaling · security, compliance, data infra · legal, accounting, operational systems
$275K – $325K
10%
Enterprise Sales & Pilots
Founder-led sales + 1–2 BD support · pre-sales engineering · convert pilots into long-term annual enterprise contracts
$175K – $225K
10%
Founder & Core Team Support
Modest founder salaries for full-time focus · early hires (support / ops) · execution velocity at scale
$175K – $225K
14 / Roadmap · 2026–27

From alpha to enterprise revenue in three phases.

A milestone-driven path from alpha stabilization through beta, public launch, and first enterprise contracts — engineered to compound momentum across the year.

Phase 01
June — August 2026
Alpha Stabilization → Beta Ready
Close out critical bugs and resolve usability gaps from design partner feedback. Lock the beta feature set and ship the first beta build to an expanded cohort. Complete Windows and Linux test passes. Begin enterprise pilot outreach to 2–5 targets.
Phase 02
August — November 2026
OS Expansion → Public Launch
Hire 2–4 engineers. Ship general-availability Windows and Linux builds. Infrastructure scaling and DevOps. Vodou OS public release. Launch initial outbound and partnership marketing strategy.
Phase 03
November 2026 — January 2027
First Enterprise Revenue → Scale & Prove
Founder-led enterprise sales with BD support. Deliver first pilot proposals. Convert pilots into annual contracts. Scale paying user base. Begin Series A preparation.
15 / Team

Built by operators who've shipped systems.

A team focused on turning AI into a system that works, scales, and delivers real outcomes — bringing together engineering, product, and business leadership with experience across enterprise, startups, and emerging technologies.

Steve Pikor
CEO
Steve Pikor

Leads strategy, growth, and market positioning. Focused on enterprise adoption, partnerships, and bringing Vodou to market at scale.

Chad Priest
CTO
Chad Priest

Architect of Vodou's core platform and orchestration engine. Leads system design and technical execution from prototype to production.

Joe Sciacchitano
CPO
Joe Sciacchitano

Leads product vision and user experience. Translates complex AI capabilities into intuitive, scalable workflows for real-world use.

James Abraham
COO
James Abraham

Oversees operations, financial strategy, and execution. Drives organizational structure, partnerships, and scalability across the business.

Become the
infrastructure layer.

The operating intelligence layer individuals and organizations eventually run on. Let's build it together. Meet Vodou — let's accelerate what the world's boldest AI builders can create.

Contact → Request a live demo