How ForeFront Power moved a 300-page solar proposal boilerplate into Inventive AI

A three-person RFP team now shreds long municipal solicitations and drafts proposals from one knowledge hub.

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300-Page Boilerplate Retired

The master Word document became a tagged, searchable knowledge hub.

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1–2 Weeks to First Live Project

From signature to the first live project in under two weeks.

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Outlines Built Automatically

Shredding turns a full municipal RFP into an outline and first draft.

ForeFront Power and Inventive AI case study cover

For ForeFront Power, a renewable energy developer owned by Mitsui, nearly every new project starts with a long-form RFP from a city, county or school district. Its three-person RFP team was building each response by copying sections out of one 300-page Word document. With Inventive AI as its RFP software, the team now shreds each solicitation and drafts from a single source of truth. This case study is based on conversations with Sunnie Zhang, former RFP Lead, and Misty Chioffe, Head of Marketing and Communications, at ForeFront Power.

Impact at a Glance

About ForeFront Power

ForeFront Power impact at a glance: A Lean Team, Rebuilt From One Document

ForeFront Power is a renewable energy developer owned by Mitsui. It builds solar, battery storage and EV charging projects for cities, counties, school districts and commercial customers across the US, and a core team of three handles its long-form proposals.

The challenge: a 300-page copy-paste nightmare

For US renewable energy projects, nearly every deal starts with a long-form RFP from a municipality or school district, usually on a tight deadline.

Before Inventive AI, every response started from one 300-page master Word document holding the company's narrative, graphics and tables. Deleting irrelevant sections took longer than copying the useful ones, so the team started each proposal from a blank page and copied sections over by hand. Over time, the master document went stale.

"This new boilerplate updated format, which is like the 300 page that I always talk about, where we have almost all of our boilerplate narrative language and graphics and tables... this is probably going to be a bigger headache because as we respond to RFPs, this is kind of outdated."
— Sunnie Zhang, former RFP Lead, ForeFront Power

The team needed proposal software for renewable energy developers that could handle long, unstructured narratives as well as standard security spreadsheets.

The solution: smarter shredding for long-form narrative proposals

ForeFront Power chose Inventive AI as its RFP software for long-form narrative proposals. Within two weeks, the 300-page boilerplate was loaded into the knowledge hub, split by business unit and tagged by US region, so the AI pulls the right content for each bid.

The turning point came when the team used Inventive AI as an RFP shredding tool on a complex municipal RFP. The AI read the full solicitation, built the outline and generated the first draft, work the team used to do by hand.

"The good thing that Inventive has done is creating that outline, so the shredding process is very smooth compared to other tools that I've trialed. Creating that first draft without formatting was really easy."
— Sunnie Zhang, former RFP Lead, ForeFront Power

Why ForeFront Power's RFP team valued the partnership with Inventive AI

For a small team, formatting was eating time that should have gone into the proposal itself. As RFP software for small marketing teams, Inventive AI now exports drafts straight into ForeFront Power's branded Word template, keeping its fonts, colors and heading styles.

"I think this looks great, what you're sharing on the screen right now. Very excited to see that... We'll be excited to start incorporating those and see if we can maybe have some broader adoption across the organization."
— Misty Chioffe, Head of Marketing and Communications, ForeFront Power

The team also got a partner that shipped updates based on its feedback, so the platform kept pace with what ForeFront Power needed.

"I think the overall communication has been great. You guys have been patient with all of our questions and trial period and everything. So, I really appreciate you all."
— Sunnie Zhang, former RFP Lead, ForeFront Power

Turn a 300-page boilerplate into a working knowledge hub with Inventive AI

Inventive AI helps lean marketing and proposal teams shred long RFPs and draft narrative responses from approved content.

Book a demo to see how Inventive AI handles proposals like ForeFront Power's.

Frequently Asked Questions

Does RFP software work for long-form narrative proposals, not just Q&A spreadsheets?

Yes, if it can read a full solicitation and draft prose sections. ForeFront Power uses Inventive AI for narrative proposals to municipalities and school districts, where most of the response is written sections instead of short answers in a spreadsheet.

Can RFP software export into a branded Word template?

Yes. Inventive AI can export drafts into a company's own Word template, keeping its fonts, colors and heading styles, so the team doesn't reformat every proposal by hand.

What is the best RFP shredding tool for a lean marketing team?

One that turns a long solicitation into an outline and first draft without a manual parsing step. ForeFront Power's RFP manager found Inventive AI's shredding smoother than the other tools she had trialed.

What is RFP shredding?

RFP shredding means breaking a solicitation into its individual requirements, instructions and evaluation criteria, then mapping each one to a section of the response. It's the step that makes sure nothing the buyer asked for gets missed.

How do you turn a master boilerplate document into a knowledge base?

Load it into an AI knowledge hub instead of copying from it, then split it by business unit or product and tag sections by region or use case. The AI can then pull only the content that fits each bid.

How long does it take to implement AI RFP software?

It depends on how much content needs restructuring. ForeFront Power went from signature to its first live project in 1–2 weeks, including loading its 300-page boilerplate.