Bootup Studios

One Sentence

Bootup Studios gives every business owner pre-built AI agents (configured by talking to them or dragging and dropping, no code, no technical configuration required) to optimize their business model, find customers, and automate the day to day processes.

The Category

Applied AI. Not competing for spend that already exists, going after the tens of millions of people who want to integrate AI into their businesses and don't have the technical background to turn a foundation model into something that works for them.

A Metaphor

Pre-built agents, custom-fit to your business the moment you talk to them or drag a block into place. No technical configuration required.

ICP

Two audiences. The narrowest is U.S. solopreneurs (29.8 million people running a business alone, generating $1.7 trillion a year, 6.8% of the U.S. economy). 81.9% of small businesses in the U.S. have zero employees. Reached through economic development orgs and employers who already serve them.

Knowledge Edge

Under 3% of Americans pay for any AI tool. Only 14% of small businesses using AI have it built into daily operations. Everyone knows ChatGPT. Foundation models get a technologist 80% of the way to something real, and the average business owner doesn't have the time, the technical background, or the desire to close that last 20%.

Distribution Edge

14 institutional customers (economic development orgs and employers) under contract. These organizations already have budget, a mandate, and a community that needs this.

White-Space

Foundation model companies build incredible tools for people who already know how to prompt, chain, and configure agents. That gets a technologist about 80% of the way to something real. The average business owner doesn't have the time, the technical background, or the desire to close that last 20% on their own. That pre-built-but-customizable layer is starting to exist, but nobody's building it specifically for entrepreneurs; it's general business-task automation, not something that validates an idea, builds a roadmap, finds customers, and connects you to funding in one place.

Alternatives

What Happens to the Gap

Any of these alternatives could add business model optimization, a roadmap, and funding-matching and come straight at this; several are well enough funded to try. No technology moat against that. What exists instead: distribution (14 institutional relationships with budget and a reason to say yes) and a vertical focus that a horizontal platform has no reason to narrow into.

Why Now

Frontier models now get a technologist most of the way to a working agentic system. What hasn't existed until now is the layer that makes that capability usable by natural language and drag-and-drop for someone with zero technical background: pre-built, but customizable. GPT-4-class inference dropped from around $30 per million tokens to under fifty cents in two years, a 95% drop, closer to 1,000x over three years. Running a full multi-agent team per customer wasn't economically possible at consumer prices two years ago. It is now.

The Math

At a $200/year reference price, U.S.: 36.2M SMBs → $7.2B annual U.S. TAM. Global: 582M SMBs → $116B+ annual global TAM. Institutional layer, adjacent: $50B+ a year in U.S. spend by economic development orgs and employers. $1.35M of that is already active pipeline across 23 named institutional opportunities, on top of $889,450 already booked.

Comparable Businesses

Median gross margin across B2B SaaS is 77%. AI-native products run about five points lower on inference cost, 63 to 68% is what public companies with AI features report. Blended margin here is 67.6%, already in that band. Vertical AI agents pulled 55.7% of all agentic-AI venture capital over the past 12 months.

Demo

A real product video, the Hero Tour, shows the product across six beats: AI-generated business model options, an auto-tracked weekly plan, and a matched Resource Hub of grants and credits, inside a real project called Coffee Roastery. Being extended to show the configuration moment directly: someone typing plain language into an agent and watching it build.

What The Agents Do

• Idea Validation: AI-assisted market analysis matching ideas to strengths and real market opportunities.
• Execution Roadmap: daily tasks, milestones, and KPIs, updated in real time.
• Lead Generation: AI-powered customer research, exportable, to find the first 100 customers.
• AI Agent Team: pre-built agents for ops, GTM, and product, configurable to the business, always on.
• Resource Hub: $100M+ in funding opportunities plus $1.5M+ in platform credits.

Proof Point

All 56 students in Morehouse College's Startup Studio Launch48 challenge used Bootup Studios as their AI-powered chief of staff. One student, Robert Robinson Jr., used it to nearly fully automate his security venture, New Age Security.

$1M in monthly recurring revenue within 24 to 36 months, scaling from there. From July's $153,500 in recognized revenue, that takes 8.1% monthly growth on a 24-month path, 6.4% on 30 months, or 5.3% on 36 months. At the current 67.6% blended margin, $1M MRR is roughly $8.1M a year in EBITDA. Even the slowest path reaches close to $3M in EBITDA by end of 2027. 5 to 8% growth every month for two to three years is aggressive but doable.

What's Real

• $889,450 in revenue across 9 months, Nov 2025–Jul 2026, best month $165K in April.
• 14 signed institutional contracts including Lightship Foundation, Omaha 100, Black Tech Initiative, Morehouse College, University of Tulsa, Arizona State University, and 8 others.
• 3,239 total active users: 2,135 B2B annual, 314 B2C annual, 368 monthly active users as of 08.19.2026.
• 83% monthly B2C retention.
• $1.35M in active B2B pipeline across 23 opportunities.

Usage is concentrated: the top 3.5% of users drive 98% of total usage. B2B engagement is 56% after the first month, against 83% on B2C. At least one institutional deployment, Morehouse, saw engagement drop below 4% after month one, part of why new university deals stopped being pursued. Revenue and paying customers are real; usage is not yet broad.

Price

Per-User Economics (from actual bank statements: Anthropic + OpenAI as inference, Rippling + Deel as human cost, blended over nine months, divided across 3,239 users)

Margin Trajectory

Blended margin over 11 months: 67.6%. By month: April 84.1%, May 83.2%, June 30.9% (Omaha 100 contract timing, not the business), July 66.3%. Recent clean months are inside the 70–80% range.

The Real P&L

Sep 2025–Jul 2026: $889,450 revenue, $288,360 operating expenses, $601,090 operating income. Cash on hand ties to every reported month-end figure: $529,340 in June, $681,090 in July.

12-Month Build (base case, 30-month path to $1M MRR, 97.5% contribution margin, fixed costs from July's actual $45,250/month growing 3%/month)

The $10M-EBITDA Path

At today's unit economics, $10M a year in EBITDA takes about 38,000 total users, 11.7x today. If that comes entirely from replicating the institutional playbook at today's average of 152 users per contract, that's 242 institutional contracts against the 14 signed, 17.3x. While doable through institutional growth alone, larger average contracts and the D2C engine doing real work will accelerate our ability to get there.

Capital

$30,000 from friends and family, fully in hand since September. $100,000 committed from PRSTRT, $50,000 of which has been wired, the rest outstanding. $80,000 received against $130,000 committed. All funds are raised on SAFEs, with the PRSTRT SAFE being uncapped.

Every institutional customer runs annual cohorts through the platform. The longer they stay, the more cohort history and ROI reporting stacks up, and the harder they are to replace at renewal. Underneath every institutional contract, the B2C base (368 monthly active, 83% retention) feeds awareness back into new institutional deals.

Asymmetric Upside

The usage-based pricing model is the compounding engine. Because revenue scales with actual usage, not a flat seat fee, a success story is worth far more than the average account. When a customer's business takes off and they lean on the agents harder, token usage climbs and so does revenue, with no incremental sales motion required. The same customer who paid $15.99 a month in their first week can generate many multiples of that once the product is doing real work for them. That's asymmetric upside: the business captures more value exactly when it delivers more value, and the upside per engaged user has no ceiling while the downside stays capped at near-zero marginal cost.

The Wedge

Two engines. The institutional engine is proven: Omaha 100 is a signed template (100 businesses, a two-year pilot), scaled by replicating across other CDFIs and the SBDC network, 900+ centers reaching about a million small businesses a year. The D2C engine is earlier; email lists and social posts have converted signups off the Resource Hub hook, but creator campaigns and UGC haven't been run yet. The two aren't separate bets: D2C builds awareness that feeds the B2B pipeline.

Pricing Wedge

The free, usage-based tier is the entry point (no subscription, pay only for usage), the on-ramp into Launch and Growth, and on the institutional side, into multi-seat contracts.

Stickiness

B2C retains well: 83% monthly. Only 56% of B2B accounts are still active a month after signup, and usage is concentrated, the top 3.5% of all users drive 98% of total usage. The renewal moat only holds if B2B accounts get used day to day, not confirmed yet beyond a handful of engaged accounts.

Five Years Out

Bootup Studios becomes the default infrastructure for people building a business without a technical team behind them. The institutional side gives economic development orgs and employers a reason to renew every year. Underneath it, the D2C engine keeps growing on its own and feeds new institutional deals. The company stays lean by design: agents do the operational work, the team stays small, and the role shifts from running the business day to day to setting direction and personally backing other entrepreneurs.

Why Me, Why This

Three-time venture-backed entrepreneur in Future of Work and EdTech. Grown two companies to seven-figure annual revenue run rates. Angel investor in acquired web3 and EdTech companies. David Kossia, co-founder and CTO, was a Senior AI Engineer at Outlier before its acquisition by Scale AI, a UT Austin computer science graduate, and the architect of the full AI agent stack running underneath the product, live since the 2025 launch.

The Team

• CEO/Sales: Chandler Malone.
• Product/Delivery: David Kossia.
• Ops/Finance: Chandler, for now, not filling the seat with anyone average; two people worth bringing in are Pryce Adade-Yebesi (founder and CEO of Open Ledger, acquired by Collective in 2026; previously co-founder and COO of Utopia Labs, acquired by Coinbase in 2025) for product or advisory, and a former COO of an international accelerator program, in network for nine years, for a COO or chief-of-staff role.

What Changed

Three institutional contracts didn't renew (Morehouse College and University of Tulsa), and University at Buffalo never closed, for budget reasons. Universities look good on paper but are boxed in by academic-year budget cycles and don't have the day-to-day muscle to drive usage the way an economic development org or employer does. On top of that, most students don't have the motivation to build an entire business, and the ones who do aren't our target customer. Full exit from universities as a core ICP. Arizona State is the one exception; they renewed. Forward-looking growth goes to economic development orgs and employers.

What Has to Be True

The company supporting entrepreneurs at scale with minimum headcount: the product doing the operational work, not a growing team. The role is setting direction, not outreach or day-to-day execution. Financially: the company generating a minimum of $1M a month, and taking home the equivalent of $1M a year. During that stretch, the bandwidth to personally back other entrepreneurs.

The Thing I'd Rather Not Say Out Loud

Usage is dangerously concentrated: the top 3.5% of users drive over 98% of total usage. Only 56% of B2B accounts are still active a month after signup, and Morehouse dropped below 4% engagement after the first month. Revenue and paying customers are real, but a meaningful share of the seats sold aren't being used the way they need to be. The product still needs to get stickier.

On Myself

I built a venture-backed bootcamp business that went out of business as GenAI came to market, the interest rate environment changed, and Elon changed the culture around headcount after laying off 75% of the team at X while the company continued forward. That gave me direct, painful insight into what AI is going to continue to do to the labor market. My time as co-founder and CEO of Path AI Test Prep showed me how much more agency entrepreneurs have in this age of GenAI; I saw firsthand how much less it took us to get a more technical product out and start scaling. Feedback is a real strength; competitive sports at a high level as a kid and through college trained that in, along with resilience, a high tolerance for pain, and a real understanding of delayed gratification. The relationship side is the real gap; moved forward with people before when the signs said not to, and it's cost me. Confident in getting this company past $1M in MRR in the next 36 months.

The Ask

• D2C growth and paid-acquisition expertise: Jesse Pujji built his career on DTC performance marketing at Ampush, a direct match for the biggest open question named above.
• Warm introductions into the institutional network being expanded into (other CDFIs and the SBDC network), help moving faster on a motion already proven with Omaha 100.
• Access to operators like Pryce Adade-Yebesi, who built tools for SMBs at Open Ledger and sold the company to Collective, a business building tools for solopreneurs; the exact path this company is on.