Investor FAQ
Product & Technology
1. What makes Brunelly different from GitHub Copilot, Cursor, or Devin?
Those tools do code generation - roughly 25-30% of the software development lifecycle. Brunelly covers the entire lifecycle: ideation, backlog generation, estimation, sprint planning, architecture, code generation, PR creation, code review, security scanning, quality analysis, bug detection, and test management. That is not an incremental difference; it is a different product category. Copilot improves code writing by 30-50%, but code writing is 25% of the SDLC. That translates to a 7.5-12.5% overall improvement. Brunelly targets 30-50% improvement across 100% of the SDLC - 3-4x the delivered value. Publicis Sapient evaluated Google, EPAM, and internal efforts for Deutsche Bank and concluded nothing matches this.
2. Why build your own AI engine instead of using existing APIs directly?
Because wrapping an LLM API is not defensible. Any competent engineer can build a ChatGPT wrapper in weeks. Maitento is a genuine AI operating system: a proprietary programming language (Cogniscript) with a complete compilation pipeline and bytecode VM, a four-type memory system (The Loom) with salience-based retrieval and decay rates, four distinct multi-agent orchestration patterns, and a syscall architecture for safe sandboxed execution. This is the architecture that enables pause/resume for human-in-the-loop workflows, deep project context across the entire lifecycle, and deterministic, observable AI execution. None of that is possible by calling an API. Independent assessment scores: Novelty 8/10, Defensibility 8.5/10.
3. How dependent are you on OpenAI or Anthropic?
Structurally mitigated. Maitento abstracts all LLM interactions behind a unified interface. We currently support Anthropic Claude, OpenAI GPT, Google Gemini, and local models via Ollama. We can switch or blend providers without application-level changes, and we use different models for different tasks based on their strengths. The LLM is a commodity input. Our proprietary orchestration layer - the Cogniscript VM, The Loom, multi-agent coordination - is where the value lives. We also run our own infrastructure (200 CPU cores, 1.28TB RAM), which reduces dependency on cloud-only API access.
4. What happens if a competitor decides to build full SDLC coverage?
They would need to rebuild from scratch. Retrofitting AI across a full lifecycle product requires fundamental architectural decisions that cannot be added incrementally - Atlassian spent $2.6B on acquisitions in 2025 trying to bolt AI onto 20-year-old tools and still does not have it. Building a comparable system from the ground up takes an experienced team 12-24 months (see Technology & IP Overview, Section 7). By that time, we will have enterprise customers, proven workflows, accumulated domain knowledge, and a 3+ year head start. The moat deepens with usage - enterprise customers with integrated workflows, custom configurations, and team-specific AI context do not rip and replace for a 1.0 competitor.
5. How long would it take a well-funded team to replicate Maitento?
12-24 months to build a comparable system, and 2-3 years before they could meaningfully compete with the integrated product. The barriers are not just time - they require a rare combination of OS design, compiler engineering, virtual machine architecture, AI agent orchestration, and distributed systems expertise. The components are architecturally interdependent: the VM needs the memory system, the memory system needs the orchestration patterns, the orchestration patterns need the syscall architecture. Copying one piece yields little without the others. This is not marketing language; it is a technical reality confirmed by independent assessment.
6. If AI models keep improving, does your orchestration layer become irrelevant?
The opposite. As models improve, the value of sophisticated orchestration increases. Better models produce better results when given structured workflows, project-wide context, and multi-phase execution - all things Maitento provides. A more capable model running through Maitento's multi-phase code generation (analyse codebase, implement following conventions, verify with tests, create PR) produces dramatically better output than the same model responding to a single prompt. Model improvement is a tailwind, not a threat.
7. You claim ~100% SDLC coverage - what is actually not built yet?
CI/CD pipeline integration, production monitoring, and the automated bug-fix loop are under development and targeted for completion by end of 2026 (see Technology Overview, Section 6). Everything else - planning, estimation, architecture, code generation, review, security scanning, testing - is live and in production today. The remaining pieces close the loop from production back to development. No competitor even aspires to this closed loop.
Business & Revenue
8. You have no revenue. Why should I invest now?
Because pre-revenue is the right time to invest if the signals are strong and the price is reasonable. The signals: Publicis Sapient (a $5B+ consultancy) independently validated Brunelly against Google and EPAM for Deutsche Bank and found nothing comparable. A serial exited founder grilled the team at the STEP conference and concluded: "This is genuinely one of the best products at the whole show." ~200 sign-ups from waitlist with zero marketing spend. 20+ serious leads from that same conference. The price: $8.5M pre-money for a company with a proprietary AI operating system, full-lifecycle SDLC coverage that no competitor matches, and active enterprise pipeline including a Tier 1 bank. Cursor was valued at $977M pre-revenue. Augment Code at $977M pre-revenue. We are asking for a fraction of those valuations with comparable technical depth.
9. What is your path to $1M ARR?
Three enterprise pilots converting to annual contracts at ~$250K ACV each ($750K) plus $250K in self-serve revenue over 18 months. The maths: 5 enterprise pilots in the first 6 months, 60% conversion rate yields 3 paying customers. Publicis Sapient / Deutsche Bank is already in active discussions. De Beers Group is a warm relationship via our Executive Chairman. 20+ STEP conference leads fill the remaining pipeline. Self-serve revenue builds from organic sign-ups, currently ~200 from waitlist. This is a bottom-up model based on specific, named pipeline - not a top-down TAM calculation.
10. Why $250K ACV - is that realistic for a seed-stage product?
$250K is the entry point, not the aspiration. Enterprise dev tool spend runs $3,000-$7,000 per developer per year. For a 200-developer team, that is $600K-$1.4M annually on fragmented tools. Brunelly at $250K replaces 5-8 of those tools while adding AI-native capabilities none of them offer. The pilot model is structured at the VP-approval level ($50K-$250K) specifically to avoid board-level procurement cycles. Our team has direct experience selling and delivering enterprise contracts at this price point through Pina Vida, which grew to 7-figure consultancy revenue.
11. How do you justify an $8.5M pre-money with no revenue?
By the assets. Two separate production codebases (Brunelly and Maitento) that would cost a funded startup $3-5M to build. A proprietary AI operating system with independent defensibility scores of 8-8.5/10. The only product on the market covering the full SDLC with AI native throughout. A pipeline that includes a $5B+ consultancy actively evaluating the product for a Tier 1 bank. And a team with enterprise delivery track record. For context, Augment Code was valued at $977M pre-revenue on IP and team alone. $8.5M pre-money for comparable technical depth with stronger enterprise validation is a reasonable entry point.
12. What is your gross margin on AI operations?
Estimated 55-70% at the Business tier ($79/user/month), which is the primary revenue tier. Typical AI inference cost per user is $15-$35/month, plus $5-$10 in non-AI platform costs, against $79 revenue. Enterprise tier ($139/user/month) margins are 60-78%. The hybrid infrastructure model (owned data centre at $300/month plus $300/month Azure) gives us a structural cost advantage - comparable cloud-only startups spend $10,000-$50,000/month on infrastructure. Margins improve with scale as fixed infrastructure costs are amortised across more users.
13. What is the revenue mix between enterprise and self-serve?
Target is 70% enterprise / 30% self-serve. Enterprise provides the predictable, high-value ARR that supports Series A fundraising. Self-serve provides volume, brand awareness, and a bottom-up adoption funnel that feeds enterprise leads. The free tier is a lead generation engine: developers try it, hit limits, upgrade, invite teammates, and eventually their CTO discovers the tool and asks about enterprise compliance features.
Team & Execution
14. Your CTO is a solo technical founder - what if he gets hit by a bus?
This is the number one risk we acknowledge openly (see Risk Factors, Section 9). Three mitigations. First, the codebase is well-structured with clear architecture patterns, consistent conventions, and industry-standard technology choices (Angular, ASP.NET, RabbitMQ, MongoDB) - it is engineered to be maintainable by a team, not a single-person knowledge silo. Second, expanding the development team is the top priority from this raise: product owner and 3-5 additional developers are the first hires. Third, the CEO runs all non-technical operations independently - commercial operations, customer relationships, and GTM execution do not depend on the CTO at all. The lean team got us to launch. The raise is specifically designed to distribute technical knowledge and reduce single-point-of-failure risk.
15. Your CFO is on maternity leave - is she actually involved?
Yes. Trishna is a co-founder with 10% equity. She is currently on maternity leave and will return in a part-time capacity funded by this raise. Her involvement is not decorative - she navigated Pina Vida through volatile consulting market conditions, trimming 40%+ of operating costs and applying disciplined financial management to keep the business healthy through difficult periods. She has IPO experience from large companies and a background in luxury goods (Louis Vuitton) and retail (Sainsbury's). Her return is planned and budgeted. In the interim, the capital discipline she instilled is embedded in how the company operates.
16. Why is the CEO a former Scrum Master, not a seasoned SaaS executive?
Because the CEO role at a seed-stage company is not the same as the CEO role at a Series C company. Dhilushi has an engineering background (materials engineering), oversaw portions of the Elizabeth Line / Crossrail - one of Europe's largest infrastructure projects - and has spent six years working alongside Guy, progressing from Scrum Master to Operational Manager to COO to CEO. She manages everything non-technical: operations, commercial relationships, investor communications, and GTM execution. She is a perfectionist who excels at operational detail. The enterprise delivery track record (Pina Vida to 7-figure revenue) was achieved under her operational leadership. The current leadership team is right for this stage. The team is open to hiring appropriate C-Suite members as required in future rounds beyond seed - if the company reaches the point where a seasoned SaaS executive is needed, that is a sign of success.
17. What is happening to your consultancy Pina Vida?
We saw the market shifting with AI tools transforming software delivery and made a deliberate decision to get ahead of it. Small consultancies will increasingly struggle to compete - and even AI consulting, while currently in demand, is a short-term play. The real upside is in product, not services. That is why we are putting our full focus into Brunelly.
Pina Vida is undergoing a managed, controlled closure. We are currently reducing from the full team and managing the completion of the last major project by end of June 2026. After that, Guy remains on a retainer for knowledge transfer for 18 months, which also funds his personal compensation without impacting Brunelly's burn rate.
This is not a failure - it is a strategic pivot to where the real opportunity is. Pina Vida grew to 7-figure revenue, delivered enterprise contracts, and built the IP that became Brunelly and Maitento. The lessons in enterprise sales, delivery, and financial discipline are embedded in how Brunelly operates. The consultancy served its purpose; the product company is the next chapter.
Market & Competition
18. The AI dev tools market is crowded - why will you win?
The crowded part of the market is code generation. Brunelly is not in the code generation market. We are in the full-lifecycle AI SDLC market, which has no established player. Cursor ($29B valuation), Copilot ($2B+ ARR), and Devin ($10B valuation) address ~25-30% of the SDLC. Nobody addresses the other 70%. The competitive positioning map in our Market Analysis (Section 4) shows a literal gap at the intersection of "Enterprise / Regulated" and "Full Lifecycle." Brunelly is the only product positioned there. The crowded market actually helps us - it validates enterprise demand for AI dev tools while leaving the full-lifecycle category open.
19. What if Microsoft or Atlassian just builds this?
Microsoft has Copilot (code only) and has been investing for years without achieving full-lifecycle coverage. Their strategy is to expand Copilot within the GitHub ecosystem, not rebuild a full SDLC platform. Atlassian spent $2.6B on acquisitions in 2025 alone ($1B for DX, $610M for The Browser Company) trying to add AI capabilities to 20-year-old tools. Their approach is bolt-on, not AI-native - and integration risk from assembled acquisitions is enormous. Building AI-native from the ground up requires 12-24 months even for a well-funded team, and they would be starting from zero on the AI orchestration layer that took us 2+ years to build. The more likely outcome is that one of them acquires us rather than building from scratch.
20. Why UAE and not Silicon Valley?
Deliberate strategy, not default. The UAE offers big-fish-small-pond positioning (less competition for investor attention and enterprise relationships), 9% corporate tax (significantly lower than the US or UK, maximising capital retained for growth), DIFC/ADGM legal frameworks comfortable for international investors, and growing enterprise tech investment (STEP conference alone generated 20+ serious leads). Our enterprise customers are global - Deutsche Bank, De Beers Group, and Publicis Sapient are not UAE companies. They care about product capability and compliance, not incorporation geography. If Y Combinator accepts us, we would parent in the US. Otherwise, the UAE offers a more capital-efficient path to Series A than burning through runway in San Francisco.
21. Your market size seems small for VC returns - explain.
The conservative TAM (AI developer tools market alone) is $15.7B by 2033 at 42.3% CAGR. But that understates the opportunity because Brunelly consolidates spend across multiple categories. Total enterprise developer tool spend is $84B-$196B annually (28M+ developers at $3,000-$7,000/year). The tool consolidation opportunity - replacing 5-8 fragmented tools with one platform - expands the addressable market well beyond the AI-specific number. Additionally, Maitento as a standalone AI orchestration platform is addressable in any industry needing complex AI workflows, comparable to the $10B+ AI infrastructure market. At an $8.5M pre-money valuation, even modest market capture delivers strong returns (see Exit Potential document for scenario analysis ranging from 5.0x to 100x+).
Legal & Structure
22. Why a UAE company and not US or UK?
Three reasons. Tax: 9% corporate tax preserves capital during the growth phase. Access: the Middle East enterprise market is underserved by AI development tools, and the UAE provides a natural base for regional expansion (Saudi Vision 2030, NEOM, Qatar National Vision). Cost: potential incorporation via accelerator freezone covers costs, legal, visas, and offices. The DIFC and ADGM legal frameworks are modelled on English common law and are well-understood by international investors. This is not unusual - many globally-focused startups incorporate in the UAE for exactly these reasons. If Y Combinator accepts us, we would parent in the US.
23. IP is currently in another company - how do I know the transfer will complete?
The IP transfer from Pina Vida to Brunelly is a condition precedent to investment closing. No investment funds will be deployed until the transfer is legally complete. The specifics: the technology was built entirely in-house by the founding team. There are no third-party claims. Pina Vida is being wound down - this is a clean separation, not a carve-out from an ongoing business. A temporary rights transfer contract is being executed immediately to ensure Brunelly has full operational rights during the transition period. Your investment documents will include legal confirmation of 100% IP ownership by Brunelly.
24. What is Pina Vida and how does it relate?
Pina Vida is a consultancy founded by Guy Powell in 2018 that grew to 7-figure revenue delivering enterprise software contracts. The Brunelly and Maitento IP was developed during this period. Pina Vida is being wound down as a separate entity, and all IP is transferring to the new Brunelly company. By the time investment closes, Brunelly will own 100% of all intellectual property with no licensing arrangements, no shared ownership, and no encumbrances. The only ongoing relationship is Guy's consultancy retainer, which funds his personal compensation without impacting Brunelly's burn rate.
Investment
25. What are you raising and at what terms?
$1.5M seed round at $8.5M pre-money valuation, offering 15% equity (preferred shares). This values the company at $10M post-money. Clean cap table: 50% CTO, 30% CEO, 10% CFO, 10% ESOP. No existing debt or obligations. Target close: June 2026.
26. What is the use of proceeds?
17% leadership team (CEO salary, part-time CFO), 13% engineering expansion (Sri Lanka developers, product owner), 23% go-to-market (UAE business development, events, collateral), 10% compliance and security (SOC 2, penetration testing, IP transfer legal), 13% infrastructure (UAE data centre, capacity expansion), 10% operations and administration (UAE incorporation, workspace), and 13% contingency reserve. The full breakdown is in the Use of Proceeds document with milestone-linked deployment across three phases.
27. When do you expect to raise Series A?
18 months post-close, approximately Q4 2027. Series A targets: ~$1M ARR, 3+ paying enterprise clients at ~$250K ACV, proven pilot-to-paid conversion model, net revenue retention above 100%, and a validated consultancy channel partnership. The $200K reserve ensures 6+ months of additional runway beyond this timeline, so we are never raising from desperation.
28. What happens if you do not hit your targets?
The downside is protected by capital efficiency. Even if enterprise sales take longer than planned, the $1.5M provides 3+ years of runway at current burn rates. The dual revenue model (enterprise + self-serve) means total revenue failure would require both motions to miss simultaneously. If enterprise pilots take 12 months instead of 6, we have the runway to wait. If conversion rates are 40% instead of 60%, we still hit $500K ARR from enterprise alone. The 13% contingency reserve exists specifically for scenario adjustment. And at worst case, the technology assets (Maitento AI OS + Brunelly platform) have standalone acquisition value - as demonstrated by Google paying $2.4B for Windsurf's technology licence alone.
29. Why not bootstrap longer?
Because the window is 12-18 months. Atlassian is spending billions on acquisitions. ClickUp acquired Codegen. Microsoft is predicted to acquire an AI coding startup in 2026. The full-lifecycle AI SDLC category is uncontested right now, but it will not stay that way. Enterprise pilot opportunities (Publicis Sapient / Deutsche Bank, De Beers Group, STEP pipeline) have a shelf life - these organisations are actively evaluating solutions and will choose something. Capital enables us to hire the team to support enterprise pilots, achieve SOC 2 certification to unblock procurement, and build the GTM motion to convert pipeline before the window closes. We have proven we can build on almost nothing. The raise is about capturing the market opportunity at the right time, not about survival.
30. What are the biggest risks I should be aware of?
We outline ten specific risks in the Risk Factors document, and we encourage you to read it in full. The top three: (1) Pre-revenue risk - strong signals but no signed contracts yet. (2) Key person risk - technical architecture concentrated in one founder, which we are mitigating with team expansion as the top use of proceeds. (3) Enterprise sales cycle risk - deals take 6-18 months, and timing is inherently unpredictable. What offsets these: extraordinary capital efficiency (3+ years runway), independent third-party validation (Publicis Sapient), a technical moat estimated at 12-24 months to replicate, and a team with proven enterprise delivery track record.
This document is confidential and intended for prospective investors only.