Accelerate Your Roadmap.
Ship in Weeks.
Deploy AI agents into Slack, Linear, and GitHub with enterprise-grade controls. Or bring in our engineers to build your product from scratch.
Trusted by teams shipping real products.
Featured in Apple Keynote.
Pick Your Path to Shipping Faster
NEW AI WORKFORCE
Build Your Own AI Workforce
Deploy AI agents that handle engineering tasks end to end, backed by senior engineers who step in when they're needed most. Scale your output without scaling your team.
PRODUCT STUDIO
Hire a Full-Stack Product Team
Our engineers own your product delivery from architecture through launch, amplified by AI at every step. The team you'd build if you had six months and a perfect hiring pipeline.
Not sure which fits? Start a conversation and we'll figure it out together.
HOW IT WORKS
Your AI workforce in 4 steps
CHOOSE YOUR DEPLOYMENT
On-premises for enterprise security. Managed cloud for speed.
SELECT YOUR TEAM
Code reviewers. DevOps. QA. PM. Pick the roles you need.
CONNECT YOUR TOOLS
We integrate with Slack, Linear, GitHub, Jira. Wherever your team already works.
LAUNCH & ITERATE
We deploy, train on your workflow, and keep improving. You get better every week.
YOUR NEW TEAM
AI agents trained for real work
CODE REVIEWER
PR reviews in minutes. Context-aware bug detection.
DEVOPS ENGINEER
CI/CD pipelines. Infrastructure as code. Deployment automation.
QA ANALYST
Test coverage. Regression prevention. Quality gates.
PROJECT MANAGER
Ticket triage. Sprint planning. Status updates.
TECHNICAL WRITER
Documentation. API references. Changelogs.
SECURITY AUDITOR
Vulnerability scanning. Compliance checks.
TRUST & CONTROLS
Enterprise Controls That Scale
AI is powerful. But power without controls is liability. Every RocketFuel AI workforce comes with the operational infrastructure serious teams require.
AUDIT LOGS
Every agent action logged, traceable, accountable. Know exactly what your AI team did, when, and why.
MISSION CONTROL DASHBOARD
Real-time visibility into your AI workforce. Task status. Performance metrics. Activity feeds.
APPROVAL GATES
Define which tasks need human sign-off. Start conservative. Expand autonomy as trust builds.
BRANCH PROTECTIONS
Agents work in isolated branches. Nothing merges without your review workflow.
COST CONTROLS
Budget caps and usage alerts. No surprise compute bills.
ESCALATION PATHS
When agents get stuck, they escalate to named engineers. Not a ticket queue. Real humans, real response times.
3
Active
2
Reviewing
47
Completed
1
Escalated
Activity Feed
Pending Approvals (2)
YOUR A-TEAM
Expert Oversight, Built In
You don't need a bigger engineering team. You need a better system. That's an AI workforce with humans in the loop: engineers who know your codebase, respond to escalations, and continuously train your agents on what works.
These aren't support staff. They're the same senior engineers who built token launch infrastructure for Collab.Land, shipped AR experiences for the NFL, and architected Web3 platforms for Hume. When they back your AI workforce, they bring that depth. When you need them to build something directly, they bring that too.
We train agents on your workflow. Not a one-time setup. Not a rigid framework. We iterate with you, tuning agent behavior, expanding capabilities, refining outputs, until your AI team operates exactly how you need.
The People Behind Your AI Team
Victor
Architecture
Harry
Infrastructure
Dimitris
3D / Immersive
Chris
Product Ops
Alex
Web3 Full-Stack
George
AI Full-Stack
Mickael
Quality Assurance
PRODUCT STUDIO
Beyond AI agents
Before we built AI workforces, we built products. Since 2019, our team has shipped token launch platforms, 5G AR experiences, Web3 music ecosystems, and enterprise tools used by millions. That track record is what makes our AI agents credible. And it's still available to you directly.
Need something built from the ground up? Our engineers work embedded with your team, from architecture through launch. Same people. Same standards. Full ownership of delivery.
CUSTOM DEVELOPMENT
Full-stack product engineering. Web, mobile, and backend systems built for scale.
WEB3 & DEFI
Token infrastructure, smart contracts, NFT platforms, decentralized applications.
AR/VR & IMMERSIVE
Augmented reality experiences, 3D platforms, spatial computing applications.
ENTERPRISE PLATFORMS
Admin systems, data pipelines, internal tools, API architectures.
Many teams start with a product build, then transition to an AI workforce for ongoing development and maintenance.
PROVEN IN PRODUCTION
Shipped by our team
TOKEN LAUNCH INFRASTRUCTURE
Collab.Land needed to launch tokens to 2M+ wallets. We built the claim site, command center, and marketplace.
8M+ connected wallets. 80M+ Discord reach.
Case Study Coming SoonWEB3 MUSIC PLATFORM
Hume needed fans to shape metastar lives in real-time. We built The Spot, NFT drops, and integrated Admin CMS.
10+ successful drops. Featured on Base chain.
Case Study Coming Soon5G AR EXPERIENCE
Verizon needed an AR fan experience for NFL 5G launch. We built the iOS/Android app with patented field tracking.
Featured in Apple 2020 Keynote.
Case Study Coming SoonQuestions You're Already Asking
Why not just use Devin / Factory / Cursor?
Those are great tools. We use some of them ourselves. But tools need deployment. They need to plug into YOUR Jira, YOUR Slack, YOUR GitHub workflows. Someone has to configure approval gates, watch output quality, and jump in when things go sideways. That's us. We're not the hammer, we're the construction crew.
How do you prevent bad code from shipping?
The same way any good engineering team does: - Agents work in branches, never main - PRs require review (human or senior agent) - Approval gates on high-risk operations - Audit logs on every action - Rollback capability on everything You set the boundaries. We enforce them.
What about security and IP?
We have options for every risk profile: - On-premises deployment. Your infrastructure, your data - Private model fine-tuning. Nothing leaves your environment - SOC 2-aligned practices - NDA and IP assignment standard in every engagement We will figure out the right setup on your first call.
What happens when an agent gets stuck?
It escalates. Not to a ticket queue. To your named A-Team engineer. Response time: 48 hours max, usually same-day. Critical issues get a direct line to your account lead. This is not fire-and-forget. It is a partnership.
Is this just a wrapper around ChatGPT?
No. We orchestrate multiple models, tools, and custom-trained agents to handle real engineering workflows. Think of it like comparing a Formula 1 team to an engine manufacturer. The engine matters, but the car, the driver, and the pit crew are what win races.
Can you just build the product for us?
Yes. Our Product Studio handles full-stack development, from architecture through launch. Web3 platforms, AR/VR experiences, enterprise systems, we've shipped all of them. Many clients start with a product build, then deploy an AI workforce for ongoing development. Others use both simultaneously. We'll figure out the right model on our first call.
How do the two modes work together?
Think of it as a spectrum. On one end, our engineers build your product directly. On the other, AI agents handle the day-to-day work with our engineers stepping in as needed. Most engagements land somewhere in between: we might build your MVP, then deploy an AI workforce to iterate on it. Or your in-house team leads development while our AI agents handle code review, testing, and documentation. We design the right mix based on what you're shipping and how your team works.
FROM CALL TO LAUNCH
We move fast
Here's what to expect:
Managed Cloud
Setup in 2 weeks. Full autonomy by week 4.
On-Premises / Enterprise
Live in 8 weeks. Full autonomy by month 3.
Product Studio
MVP in 10-12 weeks. Production-ready with handoff.
HOW PRICING WORKS
Transparent, flexible, built for value
Whether you're deploying an AI workforce or engaging our Product Studio, pricing reflects the scope and complexity of your needs. No surprises. No hourly billing traps.
AI Workforce
BASE PLATFORM
Your AI team deployment. Roles, integrations, infrastructure.
Depends on: team size, deployment model, tools connected.
USAGE
Agent compute and model costs.
Scales with: volume of work, complexity of tasks.
A-TEAM SUPPORT
Human oversight, escalation response, workflow training.
Depends on: support tier, response time requirements.
Product Studio
SCOPE DEFINITION
Clear deliverables and milestones defined upfront.
No vague estimates. No moving targets.
FIXED TIMELINE
Budget and schedule agreed before work begins.
Depends on: project complexity, team size required.
NO SCOPE CREEP
Changes require mutual agreement and re-scoping.
Protects both sides from runaway costs.
Most teams see ROI within the first month. A typical AI Workforce engagement costs less than one senior hire and ships more than a full team.
Ready?
Whether you need an AI workforce to multiply your team's output or engineers to build your next product, we're ready.
Let's figure out the right model for you.
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