Headline & intro
AI tools already write our code, slides and marketing copy. The last expensive fortress has been "thinking" itself: strategy, positioning, pricing – the work you hire McKinsey or BCG to do. Indian startup Rocket is openly attacking that fortress.
By promising "McKinsey‑style" reports for a subscription that costs less than a single consulting hour in London or Berlin, Rocket is testing how far we are willing to let AI into the boardroom. In this piece we’ll look at what Rocket is actually doing, who should care, how credible its promise is – and what this means for consultants, founders and European regulators.
The news in brief
According to TechCrunch, Indian startup Rocket, based in Surat with operations in Palo Alto, has launched Rocket 1.0, an AI platform that generates consulting‑like product strategy documents. From a simple prompt, Rocket produces PDF-style product requirement and strategy packs that cover features, pricing, unit economics and go‑to‑market ideas, and it can track competitors’ website and traffic changes.
The company says it pulls from more than 1,000 data sources, including Meta’s ad libraries, Similarweb’s API and its own web crawlers. Pricing starts around $25 per month for basic app‑building workflows, $250 for strategy and research, and $350 for the full stack including competitive intelligence.
Rocket raised a $15 million seed round in September from Accel, Salesforce Ventures and Together Fund. It claims user growth from 400,000 to over 1.5 million across 180 countries, annualised average revenue per user around $4,000, gross margins above 50% and a customer base where roughly a fifth to a third are SMEs.
Why this matters
Rocket is not just yet another AI assistant; it is attacking one of the highest-margin businesses on earth: management consulting. When an automated tool offers two or three strategy reports for $250 a month, it is implicitly asking clients why they still pay five or six figures for decks built by sleep‑deprived MBAs.
The first clear winners are early‑stage founders and resource‑constrained product teams. For many startups, the choice is not "McKinsey vs Rocket" but "Rocket vs nothing". These companies cannot afford a boutique consultancy but still need structured thinking around market sizing, pricing and competitive positioning. Even if Rocket’s output is 60–70% right, it dramatically raises the baseline quality of their planning.
SMBs also stand to benefit. A European mid‑market manufacturer or SaaS vendor can use Rocket as a fast way to test new product ideas or international expansion scenarios before spending serious money on agencies or hiring a full‑blown strategy head.
Who loses? Traditional consulting firms don’t face an immediate revenue collapse – their relationships, change‑management skills and C‑suite access are still defensible. But their junior‑heavy research and slide‑building layers are directly in Rocket’s firing line. Over time, clients will ask why armies of analysts are needed when a tool can generate the first 50 slides in an afternoon.
The risk, however, is a wave of shallow, copy‑paste "strategies" based on generic data and AI hallucinations. If teams start treating Rocket’s PDFs as gospel instead of as starting points, we’ll see more beautifully formatted but fundamentally misguided product bets.
The bigger picture
Rocket sits on top of two converging trends.
First, the commoditisation of code. With tools like Replit, Cursor, GitHub Copilot and Claude Code, building a decent prototype is no longer the bottleneck. The hard question moved upstream: not "can we build it?" but "should we build it, and for whom?" Rocket is explicitly targeting that pre‑coding phase – the messy strategic discussion that typically lives in Notion docs, whiteboards and expensive workshops.
Second, the professionalisation of AI‑generated documents. We already have AI for pitch decks (Tome, Gamma), investor memos (Notion AI, custom GPTs), and market overviews (Perplexity‑powered research tools). Rocket’s twist is the tight integration of external data sources and the ambition to output something that looks like a full consulting engagement: structured, referenced, with basic unit economics.
Big consulting houses are not asleep here. McKinsey has been pushing its QuantumBlack AI practice; BCG X and Bain have their own AI co‑pilots to accelerate research and modelling. But these are internal tools to make consultants more productive, not products priced for the mass market. Rocket, by contrast, is a SaaS front door for anyone with a credit card.
Historically, software that "automates experts" rarely eliminates them; it changes who can afford them and what those experts do. QuickBooks didn’t kill accountants, Canva didn’t kill designers – but both moved expertise up‑market and expanded the overall market. Expect something similar: AI strategy tools will force consultants to focus on change management, leadership alignment and access to proprietary data, while the AI handles the generic competitor matrices and boilerplate market analysis.
The European / regional angle
For Europe, Rocket is both an opportunity and a regulatory headache.
On the opportunity side, the continent is full of SMEs and mid‑caps that are under‑served by Tier‑1 consultancies. A German Mittelstand supplier, a Slovenian SaaS startup or a Croatian tourism platform can use a tool like Rocket to approximate the kind of structured analysis usually reserved for corporates with seven‑figure consulting budgets. This could narrow the "strategy gap" between Silicon Valley scale‑ups and European companies that traditionally move more cautiously.
But the EU AI Act, GDPR and the Digital Services Act will all shape how such tools can operate here. Rocket says it aggregates data from ad libraries, web traffic tools and its own crawlers. In Europe, that raises questions around consent, profiling and web scraping of EU businesses’ data. Even if the AI system is likely classified as "limited risk" under the AI Act, providers must ensure transparency, proper data handling and straightforward opt‑out mechanisms for scraped sites.
European corporate buyers are also more conservative. Procurement teams in Frankfurt, Paris or Madrid will demand clear documentation on data provenance, model governance and bias testing long before they let AI‑generated strategy documents near their board. This plays to the strengths of local vendors and EU‑born AI startups that can design compliance‑first offerings.
Finally, language and local nuance matter. A generic AI report might misread labour law constraints in Germany, misjudge consumer credit attitudes in Spain or ignore structural issues in Eastern European markets. European users will need to treat Rocket as a powerful drafting tool, not as a substitute for on‑the‑ground expertise.
Looking ahead
The most likely short‑term outcome is not a mass exodus from consulting contracts, but a shift in how strategy work is scoped. Over the next 12–24 months expect:
- Hybrid projects: clients using Rocket‑like tools to generate initial hypotheses, with consultants brought in later to validate, enrich with proprietary data and manage execution.
- Internal "Rocket clones": larger corporates – especially in regulated industries – will build in‑house strategy copilots fine‑tuned on their internal data, rather than relying on an external SaaS from India or the U.S.
- Pricing pressure at the low end: boutique consultancies and freelance strategists doing templated market entry or product reports will feel real margin squeeze.
Key questions remain. How transparent will Rocket be about its data sources and limitations? Will it allow enterprises to plug in their own sales, CRM and support data to move from generic advice to genuinely proprietary insight? And how will liability work if an AI‑generated strategy contributes to a costly misstep?
For readers, the practical move is experimentation with guardrails. Use tools like Rocket to speed up early research, scenario thinking and document drafting – but always pair them with domain experts, local legal insight and your own customer conversations.
The bottom line
Rocket is an important signal: AI is climbing out of the code editor and into the strategy room. The promise of "McKinsey‑style" output for a few hundred dollars a month is overstated but directionally correct – much of low‑end consulting is ripe for automation.
If European founders and executives treat Rocket as a thinking partner rather than an oracle, they will gain speed without surrendering judgment. The open question is whether incumbents and regulators can adapt fast enough – or whether the next great strategic misfire will arrive, neatly formatted, as a flawless 80‑page AI‑generated PDF.
