Jean-Christophe Lanoix is the founder of Turboconsultant. He spent seventeen years at Hinicio, a strategy consultancy specialising in hydrogen — joining as an intern, rising to Associate Director and leaving in 2024, two years after the firm's exit. He now builds the system he wishes he had had.
Introducing Turboconsultant
An execution layer for solo consultants: a virtual team of AI agents spanning the whole practice — business development, research, methodologies, marketing and content, deliverable production, quality control, meetings and follow-up, admin. The consultant directs. The agents execute. It installs as a plugin on Claude Cowork and turns a generalist agentic workspace into a consulting-grade one. Three things separate it from a general-purpose assistant.
Personalisation. A one-time onboarding hands it the consultant's own methodologies, templates, frameworks and voice. What comes out arrives in their template, follows their methods, and reads in their words.
Quality control. Every document it produces passes three layers of audit before it leaves — sources traced, figures recomputed, claims contested by models outside the system. That is where AI hallucination and error get caught.
Data walling. Nothing moves from one engagement to another, and the models do not train on client work.
And it is one system rather than a patchwork of tools: the whole practice runs in a single environment that sharpens with every engagement.
The net effect, measured on the existing user base, is a 25x on average, while improving the general quality of the work.
Demonstration of Turboconsutlant
Both cases are invented, and so is the consultant behind them — a generic profile carrying no proprietary methodologies, no past deliverables, no writing to learn from. The engagement starts the way a real one does: a request for proposal lands by email. Everything that follows comes out of that one document and public sources.
The proposal — thirty minutes
The system interviews the consultant first — how they want to work, whether they know the client, who delivers, what their day rate is. Then it writes, in their own template: context, the question behind the client's question, objectives, approach and methodology, scope in and out, work packages, data room requirements, timeline, budget options, next steps. The consultant reviews and signs off. Nothing leaves unvalidated.
Without AI, a proposal of that depth is several man-days.
The methodology section — six work packages mapped onto one governing question.
Pricing the work — three options, fees, payment terms. A commercial proposal, not an analysis.
The kick-off pack — fifteen minutes
One instruction produces the whole pack: the client kick-off deck, an internal briefing note — assumptions, questions to ask, objections to expect, the landmines — and the data room request list in Excel, item by item, with what each one unblocks and the date it is needed by.
In a firm, this is junior work. A solo consultant has no junior. It costs them half a day to a full day, every time.
The work-package sequence agreed at kick-off, and the date after which the analysis stops waiting for client data.
The First Deliverable — forty-five minutes
The pattern holds whatever the sector: the research, the market sizing, the model underneath, and a deck of exhibits in the consultant's own consulting-grade template — each exhibit carrying one argument, each figure carrying its source.
This is where the consultant sits as a director rather than an executant: give the instruction, let the team execute, come back and review. It is also where the system refuses to please. Here it tested the client board's own headline figure instead of repeating it, and the deck says why.
Forty-five minutes for a work package that is easily five to ten days of work without it.
An exhibit from the first deliverable — the sizing funnel, in the consultant's template.
The economics behind it, recomputed from the model that sits under the deck.
Quality control — three layers, then a loop
Nothing reaches the client before three independent passes.
Layer 1 — sources. Every claim and every figure traced back to where it came from, the source assessed, each one rated: verified, probable, or not established.
Layer 2 — internal audit. An isolated sub-agent reviews the finished document against a purpose-built grid and rebuilds the Excel model from its own inputs. Same family of model, so it catches the obvious: the unsupported claim, the figure that contradicts the model, the page that does not carry its title.
Layer 3 — dual external audit. Two models from outside the system, independent of each other and of the one that did the work. No shared bias, and two verdicts to compare. This is where the qualitative control happens. Here the two disagreed — which is itself the finding.
Then the loop. The consultant asks the system to integrate the findings and audit again, and iterates. Half an hour takes a document from roughly 85% client-ready to something that needs only a final human review.
The three verdicts on the first draft, as returned — including the external model that said HOLD.
Everything from both engagements is published
Every file is downloadable, unedited: the proposals, the contract, the kick-off packs, the deliverables, the Excel models, and the three audit reports in full — including the one that said do not ship, and the revised deliverable it forced. A second engagement, in a different sector, was launched live during the recording; it landed after the recording stopped, and its files are there too.
Access the files: turboconsultant.com/unleashed
Timings above are the elapsed time of each task on this run, not a benchmark.
Watch the video:
Listener Offer
Are you a good fit?
· You consult on your own — strategy or management?
· You want to scale without compromising quality?
· Consumer AI gets you a draft, not a deliverable?
Three yeses? Thirty minutes with me, free. If it's not a fit, I'll tell you. → https://calendly.com/jcl-turboconsultant/unleashed?month=2026-07
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Timestamps
04:02: Turboconsultant's Features and Benefits
07:32: Onboarding and Personalization Process
12:24: Demo of Turboconsultant's Capabilities
23:42: Kickoff Meeting Preparation and Work Package Execution
43:45: Quality Assurance and Iterative Improvement
50:07: Additional Features and Conclusion
Links:
Video permalink: https://umbrex.com/wp-content/uploads/2026/08/Jean-Christophe-Lanoix.mp4
LinkedIn: https://www.linkedin.com/in/jean-christophe-lanoix-93119018 Company website: https://www.turboconsultant.com Files from this episode: https://www.turboconsultant.com/unleashed
This episode on Umbrex: https://umbrex.com/unleashed/episode-656-jean-christophe-lanoix-turboconsultant-running-a-solo-practice-on-ai-agents-end-to-end/
Unleashed is produced by Umbrex, which has a mission of connecting independent management consultants with one another, creating opportunities for members to meet, build relationships, and share lessons learned. Learn more at www.umbrex.com.
*AI generated timestamps and show notes.
