At Fulcrum, a core AI-augmented dedicated team starts at $12,000 per month. A full product team with a product owner, UI/UX designer, QA, and multiple developers costs $15,000–20,000 per month. This is typically 30–40% less than hiring equivalent in-house talent when you factor in recruiting, onboarding, benefits, and tooling costs.

We recommend a minimum 3-month engagement to see meaningful results, but there is no long-term lock-in. After the initial period, either side can end the engagement with 30 days notice.

Yes. You own 100% of the code, intellectual property, and all project artifacts from day one. This is standard in every Fulcrum engagement — it’s in the contract.

Fixed monthly pricing. You pay a predictable amount per month for a dedicated team — no hourly billing, no surprise invoices. What you see is what you pay.

No. AI tooling costs (Claude, Codex, Cursor) are included in the monthly fee. You only pay separately for your own cloud infrastructure (AWS, GCP, etc.) and any third-party SaaS licenses your product requires.

Developers receive tasks and craft instructions for AI agents instead of writing every line of code manually. AI generates code, developers review and course-correct, then AI generates tests for verification. The developer becomes an orchestrator-reviewer — managing AI output rather than writing boilerplate. This creates a ~2–3x speed improvement over traditional development.

AI agents handle routine, parallelizable tasks: generating boilerplate code, writing test suites, running automated checks, and flagging issues. They work 24/7 across multiple task streams simultaneously. Human developers focus on architecture decisions, business logic, code review, and deployment — the work that requires judgment.

Every piece of AI-generated code is reviewed by a human developer before it reaches production. We use hard quality gateways — minimum test coverage thresholds, migration checks, automated regression testing, and manual QA. The AI accelerates the process; it doesn’t bypass quality controls.

We run 2-week sprints. At the start, we plan priorities together. During the sprint, AI agents generate code in parallel while developers review, refine, and deploy. Mid-sprint you see progress in real time. At the end, we demo working features — not slides or mockups. You give feedback, we adjust, and the next sprint begins.

We follow a drop-and-restart approach rather than trying to fix bad AI output. If an agent produces low-quality code, the developer discards it and re-runs the workflow with refined instructions. This is faster and cleaner than debugging AI-generated code. Hard gateways catch quality issues before anything reaches production.

Most teams are fully onboarded within 5–7 business days. We begin with a codebase audit (if you have existing code), configure AI workflows for your stack, set up the sprint cadence, and start delivering in the first sprint. No 3-month ramp-up period.

Access to your existing codebase (if any), a product backlog or feature list, and a primary point of contact for priorities and feedback. We handle everything else — team setup, tooling, workflow configuration, and sprint planning.

Yes. We start with a codebase audit to understand your architecture, identify technical debt, and configure our AI workflows for your specific stack. We don’t require a rewrite — we adapt to what you have.

That works too. We run a 1–2 week discovery phase to define the architecture, set up the project infrastructure, configure CI/CD, and create the initial backlog. First working features are typically delivered within the first sprint after discovery.

Our teams are strongest in React, Next.js, React Native, Node.js, Python, and cloud infrastructure (AWS, GCP). Our AI agents are stack-aware and adapt to your existing codebase — we don’t force a technology change.

We primarily use Claude (for planning, code review, and architecture decisions) and Codex (for code generation and execution). Our developers also work with Cursor and other AI accelerators. The model landscape changes fast — we continuously swap in better models as they become available.

No. All AI tooling runs on our side and is included in the monthly fee. You don’t need to manage any AI infrastructure, API keys, or model subscriptions. Your codebase stays in your repository — we connect to it via standard development workflows.

Yes. We integrate with your existing project management, version control, and communication tools. Most teams use Jira or Linear for task management, GitHub or GitLab for code, and Slack for daily communication. We adapt to your setup.

Yes. After the initial 3-month period, you can adjust team size with 30 days notice. Need to add a second developer for a feature push? We can usually onboard within a week. Need to scale down after a major release? Just let us know a month ahead.

Knowledge is retained through thorough documentation, well-structured codebases, and our AI workflow configurations. Sprint histories, architecture decisions, and technical context are all documented. New team members can ramp up quickly because the AI workflows encode a lot of project-specific knowledge.

This is a real consideration. As codebases grow, test suites take longer and changes become more complex. We mitigate this through mandatory modular architecture — splitting code into small, independent packages. This keeps AI agents effective because they operate on isolated modules rather than the entire codebase.

Absolutely. You own all the code, documentation, and architecture. We provide a structured handover process including knowledge transfer sessions, architecture walkthroughs, and documentation of all AI workflows — so your in-house team can continue where we left off.

Hiring in-house typically takes 2–4 months per engineer (recruiting, interviewing, onboarding). A Fulcrum dedicated team is productive within 1 week. Cost-wise, a senior full-stack developer in the US costs $150–200K/year fully loaded — our full AI-augmented team costs $144–240K/year and delivers 2–3x more output because of AI acceleration.

Freelancers are individuals who work independently — no QA, no product owner, no design coordination. You manage them. A dedicated team from Fulcrum is a self-managed product unit with all roles included. You set priorities; we manage execution. AI augmentation adds speed that individual freelancers can’t match.

Traditional agencies bill hours and staff projects with whoever is available. We assign a stable, dedicated team to your product — same people, same codebase, same context. AI augmentation means our team ships 2–3x faster at a similar monthly cost. And our pricing is fixed, not hourly.

No. Tools like Cursor and Copilot help individual developers code faster. Our service is a full product team — humans plus AI — that takes ownership of building and maintaining your product. You don’t need to hire developers, manage AI tools, or configure workflows. We handle everything.

Yes. Our dedicated team can work alongside your in-house engineers on a shared codebase. We typically take ownership of specific features or modules while your team handles others. The AI-augmented workflow means we integrate fast without slowing down your existing team.