Technology and Innovation

Models built to bear institutional investor scrutiny across SaaS, platform, hardware and deep-tech.

What this sector typically needs

Institutional-quality financial modelling and advisory for SaaS, platform, hardware and deep-tech businesses.

Technology businesses require models that capture non-linear growth, subscription cohort economics, platform dynamics and the particular characteristics of combined hardware-software propositions. Institutional investors in the sector scrutinise unit economics, cohort retention, gross margin trajectory and capital efficiency, not headline revenue forecasts. A plausible top line built on implausible cohort behaviour will be challenged in the first investor meeting; a defensible cohort layer, with retention and expansion evidenced from the product data, will not.

Founders preparing to raise need a model that can withstand institutional questioning, a board pack that communicates clearly without resorting to vanity metrics, and a financial narrative that connects to the product and engineering plan. The three artefacts have to agree with one another. A model that produces numbers the board pack contradicts, or a narrative that the engineering roadmap cannot deliver, will not survive due diligence. The work is to make the financial story coherent across the materials a sophisticated investor will read together.

How we work in Technology and Innovation

The senior team has built production software systems, not merely modelled them from the outside. That technical literacy makes assumption challenge more credible to founders and to investors, because the questions we put back to the engineering team are the questions an experienced technical investor would put. Where the model rests on infrastructure costs, latency-driven margin behaviour or platform take-rate mechanics, we can interrogate the underlying logic rather than accepting the founder's framing.

Engagements typically wrap around a fundraise milestone. The work involves a model rebuild or remediation, a board pack produced under the new structure, and investor Q&A support through the process. Where the business is post-fundraise, the same engagement often graduates into a retained fractional CFO arrangement, with monthly board materials and rolling forecast cadence. We do not attempt to replicate venture-stage advisory generalism; we focus on the financial and analytical layer that institutional capital actually tests.

Sector-specific considerations

Cohort and retention assumptions must be evidenced from product data, not asserted. The single line in a SaaS model that most often falls over under institutional scrutiny is the assumed net revenue retention curve, because the gap between aspiration and observed cohort behaviour is usually wide. We build the cohort layer from the actuals where they exist and flag the extrapolation explicitly where they do not.

Hardware businesses require unit-economics and working capital modelling that pure-software templates handle poorly. Inventory cycles, component lead times and warranty provisions belong in the model, not in a footnote. Where the engagement touches regulated technology (fintech, health-tech, anything carrying licensing or safety obligations), we flag the regulatory considerations explicitly, name the constraint and route the regulatory question to specialist counsel rather than absorbing it into the financial layer.

Sanitised. Sector-coded. No client identification.

An engagement in Technology and Innovation

When this sector needs non-financial advisory

GIVE Consultancy, one call away

Sector engagements often surface questions that sit outside the analytical perimeter: regulatory exposure, internal communications, organisational capacity. Where that happens, GIVE Consultancy Limited, the second firm in the GIVE Network, is available under the same confidentiality regime. Both firms donate ten per cent of annual profits to the GIVE Foundation, the network's charitable entity. The arrangement is structural rather than commercial: it reflects how the firms were set up, not a referral incentive. Clients are introduced only on request, and only where the adjacent work is genuinely required.

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Confidentiality

Engagement details are not disclosed publicly. Past work is summarised by sector and analytical question. References are made available privately, with consent, at the appropriate stage. The same standard applies to anything you instruct us on.

Discuss a Technology and Innovation engagement

A 30-minute introductory call, in confidence. We will tell you if your project fits this practice.