From tech jargon to clear story: crafting an EIC ready innovation narrative

Far too many strong EIC projects fall at the first hurdle simply because evaluators just can’t follow the story. The technology is impressive, but the writing gets heavy and the key points end up buried.

That can make your application look riskier or more confusing than it really is, even when the science and business case are solid. The good news is, this is easy to fix: a clear structure and a few simple habits go a long way. You don’t need to oversimplify your work, just explain it so a busy evaluator can quickly understand and support your project.

1 | Structure of a compelling story

A clear innovation story has three parts: problem, solution, impact.

‣‣‣ Start with the problem. Who is affected? What do they struggle with? What’s at stake for them or their business? Use real examples: lost time, wasted money, extra risks, missed results. Resist the urge to lead with your technology; focus first on what your users are struggling with right now.

‣‣‣ Next, talk about your solution. In a couple of sentences, say what you’ve built and how it works in simple terms. Don’t get bogged down in every detail, just stick to the main idea. Point out what’s truly new: maybe it’s a different approach, a new mix of technologies, or a unique data source?

‣‣‣ Finally, explain the impact. Why does your solution matter now? How can it grow? Link back to the problem with clear results: lower costs, better performance, new revenue, less emissions, or improved health. End with a simple statement about how big the change could be if your project works.

2 | Translating technical depth into benefits

Your expertise is an asset, but too much detail can obscure the value. The key is to translate depth into benefits without losing credibility.

Analogies help. Compare your approach to something familiar, then point out the key difference. For example: “Think of our platform as a ‘satellite navigation system’ for hospital logistics, continuously recalculating the best route for each patient.” This gives evaluators a mental model they can hold onto.

Before/after scenarios are also powerful. Describe how a task is done today and how it will work with your solution. Quantify the change where possible. For instance: “Today, engineers need three separate tools and manual spreadsheets to plan maintenance. With our system, they use one interface that generates optimised plans in minutes.”

To keep jargon under control, ask yourself whether a smart non‑specialist would understand each sentence. Swap out the niche terms for plain language, or define them once and move on. You can always save the essential technical details in a separate section, diagram or annex, so your main story stays clear and easy to follow.

3 |   “before/after” example

Here is a typical “before” paragraph:

“Using a proprietary multi‑modal deep learning architecture, our system ingests heterogeneous sensor data streams to perform real‑time anomaly detection on industrial assets. The model has been trained on 5TB of historical data and leverages unsupervised feature extraction to identify deviations from normal operational envelopes.”

This may be technically accurate, but it forces evaluators to work hard to understand why it matters.

Here is an “after” version:

“Industrial operators currently rely on manual checks and basic alarms to spot equipment problems, which means many failures are only detected after costly downtime. Our software monitors thousands of sensor signals at once and learns what ‘normal’ behaviour looks like for each asset. When it sees an unusual pattern that usually precedes a fault, it alerts the maintenance team days or weeks in advance. In pilot projects, this has reduced unplanned downtime by 30% and cut maintenance costs by 20%.”

What changed?

  ✔  We started with the current situation and its consequences, not the algorithm.

  ✔  We explained what the system does in everyday terms: learns normal behaviour, spots unusual patterns, sends alerts.

  ✔  We kept the focus on outcomes: less downtime, lower costs.

  ✔  We removed jargon that does not directly support the funding case and left technical detail for later sections.

4 | Practical tips

Here are three quick checks you can run on your own narrative.

1)  the read‑aloud test: read key sections out loud to yourself or a colleague. If you stumble or need to explain every other sentence, it’s time to simplify.

2)  the non‑expert review: ask someone outside your field to read your one‑page summary and tell you what they think you do, why it is new and why it matters. Listen carefully to where they get lost.

3)  the one‑sentence summary: try to write a single sentence that captures problem, solution and impact. If you can’t do that yet, your narrative isn’t quite ready.

Pick a section from your EIC draft, run these tests today, and have a go at rewriting it using the problem–solution–impact structure. It’s a small step, but it’ll make your application, and your whole investment story much stronger.

We can help

At ABGi, we help companies decide if the EIC Accelerator is a good fit, develop strong proposals, and prepare for the whole process, including interviews and post-award support. This gives your application the best chance of success.

If you want personalised advice on finding funding at any stage of your innovation journey, contact the ABGI Team. We are happy to talk about your goals and explain how we can help.