Last updated: June 9, 2026

You’ve been asked to evaluate AI proposal tools for your firm. You pull up the options, and most of them look similar from the outside — AI writing, template libraries, RFP upload. Then you get into the demos. The platform with the strongest marketing was built for SaaS sales proposals. The one with 800+ G2 reviews handles security questionnaires. None of them have a Go/No-Go module or know what an SF330 is.

That’s the market you’re sorting through. This guide evaluates five AI proposal writing tools specifically for AEC:

• OpenAsset Shred
• Kantiv (formerly Joist.ai)
• Loopio
• AutogenAI, and
• Unanet GrowthStudio (formerly Unanet ProposalAI)

Each is assessed against the criteria that matter to AEC proposal teams: compliance extraction method, Go/No-Go capability, DAM integration, AEC system integrations, SF330 support, and data privacy posture.

A note on my perspective: I’m head of AEC Marketing Innovation at OpenAsset, where OpenAsset Shred is our AI proposal writing tool. I’ve used it in live proposals since launch. The other platforms in this comparison are evaluated based on publicly available information including vendor websites and user reviews.

How to evaluate AI proposal software: AEC-specific criteria

The criteria that matter for AEC proposal software aren’t the same ones a sales team would prioritize. Here are seven questions worth asking when you’re evaluating platforms.

1. DAM integration or native asset management

Does the tool connect to your existing digital asset management system, or does it require uploading assets separately for each proposal? Without DAM integration, you’re curating assets from scratch for every pursuit. Ask whether the integration is native or API-dependent. It’s not the same thing.

2. Compliance extraction method

Does the tool extract RFP requirements word-for-word, or summarize them? Verbatim extraction matters in AEC because compliance errors are disqualifying and evaluators check for specific language, not approximations.

Pro-tip: Ask each vendor directly how their compliance extraction works. Most will describe it as “AI-powered” or “intelligent.” What you need to know is whether the output is verbatim language from the RFP or a reinterpretation of it. That distinction matters more than anything else on the compliance features list.

3. Go/No-Go analysis 

Does the tool analyze your firm’s win history to score new pursuits? In my view, Go/No-Go decision frameworks that use a weighted scoring model that learns from past proposals are meaningfully different from a static template or a manual checklist. 

4. AEC-specific integrations

It’s important for AI proposal software to integrate with AEC tools like Deltek Vision, Deltek Vantagepoint, Unanet, Procore. If the tool doesn’t connect to the platforms your firm already runs, your marketing team is the one bridging the gap — manually.

5. SF330 support

For federal A/E work, SF330 qualification packages are standard. This criterion only applies if your firm pursues federal contracts. The question to ask: Does the tool understand the SF330 format and help populate it?

6. Data privacy posture

Is your firm’s proposal content used to train the vendor’s public AI models? SOC 2 Type II compliance is a minimum bar. Ask specifically whether your data is isolated and excluded from shared training — the policies vary more than the marketing language suggests.

7. Human-in-the-loop design

The best tools surface and suggest; they don’t replace judgment. You still own the strategy, voice, and final review. Look for platforms designed around that assumption, not ones that treat the marketer as optional.

Comparison: OpenAsset Shred vs. Kantiv (Joist.ai) vs. Loopio vs. AutogenAI vs. Unanet GrowthStudio

Criterion	OpenAsset Shred	Kantiv	Loopio	AutogenAI	Unanet GrowthStudio
AEC industry focus	✓ Purpose-built; OpenAsset serves 1,000+ AEC firms	✓ AEC-native; G2 reviewers visibly AEC	✗ No — SaaS, healthcare, security reviewer base	Partial — ~15–20% AEC on G2; mostly UK/EU bid teams	GovCon-primary; separate AEC product page at unanet.com/proposal-ai-aec
Native DAM integration	✓ OpenAsset DAM + Adobe InDesign drag-and-drop	✗ Salesforce and Adobe InDesign only	✗ Microsoft 365, Salesforce, Google Workspace	✗ Microsoft SharePoint/365 only	✗ Unanet CRM/ERP ecosystem only
Compliance extraction	✓ Verbatim — “key details extracted verbatim”; real-time draft compliance check	Analytical review — no reviewer in 11 G2 reviews describes verbatim extraction	Answer library auto-fill; not designed for solicitation compliance	Compliance Matrix exists; G2 reviewers say it “misses a lot of requirements”	“RFP Shredder” — structured/categorical; reviewer notes “some sections still need manual cleanup”
Go/No-Go scoring	✓ Weighted scoring model	✓ Win pattern analytics; historical pursuit tracking	✗ No	Partial — “Qualify and Extract” module	Partial — “Champ” component for pursuit strategy
AEC integrations	✓ OpenAsset DAM and Adobe InDesign. Indirect integration with Deltek, Unanet, and Procure when using OpenAsset DAM	Salesforce, Adobe InDesign confirmed; no Deltek, Unanet, or Procore in public documentation or 11 G2 reviews	No AEC integrations	No AEC integrations	Unanet CRM/ERP native only
SF330 support	Partial — Helps surface answers to complete SF330 forms but does not auto-populate forms	✓ Explicitly shown on Kantiv homepage	✗ No	✗ No — UK/EU bid vocabulary; SF330 never mentioned	Partial — Consolidates relevant information, but does not help you fill forms
AI writing assistant	✓ Proposal Studio + inline writing tool (~May 2026)	✓ First-draft generation from RFP upload	✓ “Reduced time to first draft by 70–80%” (G2 reviewer, April 2026)	✓ Ideator, Expand, Evidence features; custom language engines	✓ “Drafts are usually close to what I need” (G2 reviewer)
Analytics and pursuit insights	✗ No, but plans to add in future	✓ Win/loss patterns, client pursuit history, strategy tracking	✓ Readiness scoring, win probability metrics	Partial — ROI claims; specific analytics features unclear	Via Unanet CRM integration
SOC 2 / security	✓ SOC 2 Type II — most explicit privacy posture in this set	✓ SOC 2 + ISO 27001 + CMMC at trust.	✓ SOC 2 Type II + ISO 27001	✓ FedRAMP High + ISO 27001	✓ SOC 2 Type II + FedRAMP Moderate Equivalency
Data not used to train AI models	✓ Explicit on-record: “customer data is never used to train public models”	Not disclosed publicly; not in any of 11 G2 reviews	Not disclosed publicly	Privacy mentioned positively in reviews; no formal policy on record	“Private AI instance” in marketing only; no reviewer corroboration
G2 reviews / rating	1 review / 5.0 ★	11 reviews / 4.9 ★	~813 reviews / 4.6 ★ — G2 Leader in RFP Software	147 reviews / 4.4 ★	1 review / 4.0 ★ — Government Procurement Software
Best fit	OpenAsset DAM users; AEC-first firms needing DAM + AI in one platform	AEC firms evaluating standalone tools; strongest pursuit analytics in this set	Enterprise teams with high multi-sector RFP volume	Firms bidding across AEC and other industries; UK/EU context	AEC and GovCon firms already in the Unanet ecosystem

Tool summaries

OpenAsset Shred

OpenAsset Shred is OpenAsset’s AI-powered proposal writing tool for AEC marketing and BD teams, built by a company that has served over 1,000 AEC firms for more than 20 years. Its core differentiator is the native OpenAsset DAM integration: project photos, team bios, and past proposals stored in OpenAsset’s digital management system flow directly into proposal development without manual upload. 

OpenAsset Shred is the only tool in this comparison publicly described as performing verbatim RFP compliance extraction: a June 2025 PR Newswire announcement on the OpenAsset Shred launch describes its RFP reader as extracting “key details verbatim.” It holds the most explicit data privacy commitment in the set: customer data is never used to train public AI models.

The G2 review count (1 review, compared to 147 for AutogenAI and 800+ for Loopio) reflects OpenAsset Shred’s August 2025 launch date, not its adoption level. Named customer references Thomas & Hutton and Design Collective appear on the product page. 

Kantiv (formerly Joist.ai)

Kantiv, formerly known as Joist.ai, positions itself as a “pursuit enablement platform” and is genuinely AEC-native. Its G2 reviewer base includes civil engineers, pursuit specialists, and regional business development directors who describe it in AEC vocabulary. One reviewer writes: “It’s clear that the people at Joist understand the AEC industry.” Its pursuit analytics are very strong in this comparison: win/loss pattern tracking, historical pursuit data, and client relationship context. Kantiv holds SMPS Strategic Partner status.

However, Kantiv doesn’t have native DAM integration. No Deltek, Unanet, or Procore integrations appear in Kantiv’s public documentation or in any of the 11 G2 reviews. If those connections matter to your firm, verify directly with Joist before purchasing.

Loopio

Loopio is the most review-validated RFP platform in this set, with over 800 G2 reviews and Leader status in the RFP Software Grid. Its reviewer base is not AEC — Loopio is built for SaaS, healthcare, and security questionnaire teams. One April 2026 G2 reviewer reports that Loopio’s AI features “reduced time to first draft by about 70–80% and most of the answers are solid.”

If your firm handles significant multi-sector RFP volume and needs one platform across industries, Loopio is worth evaluating. For firms whose work is AEC-specific, Loopio lacks the industry integrations and compliance workflow that AEC proposals require.

AutogenAI

AutogenAI offers the broadest feature set in this comparison: end-to-end bid management with strong security credentials including FedRAMP High and ISO 27001. Its steepest G2 complaint is the learning curve. Eighteen reviews are tagged “challenging learning curve” and the dominant complaint is that the tool is “not intuitive.” The Compliance Matrix is reviewer-confirmed as gappy: one enterprise reviewer writes that it “misses a lot of requirements you should comply with.”

AutogenAI’s reviewer base is predominantly UK and EU bid teams. It’s not purpose-built for US AEC firms doing SF330-style federal work.

Unanet GrowthStudio

Unanet GrowthStudio (formerly Unanet ProposalAI) is the platform to evaluate if your firm is already in the Unanet ecosystem. Note the rebrand: what was Unanet ProposalAI is now bundled inside Unanet GrowthStudio, and the original G2 URL 301-redirects to the new page. Buyers searching for “Unanet ProposalAI” will encounter this redirect. OpenAsset and Unanet are integration partners. If your firm uses both platforms, evaluate GrowthStudio directly with your Unanet rep rather than treating this as a head-to-head comparison.

Which AI proposal tool is best for AEC firms?

OpenAsset Shred is the strongest fit for OpenAsset DAM users and AEC firms whose competitive differentiation comes through their project portfolios and team credentials. Kantiv is the leading standalone AEC-native option, particularly for firms that prioritize pursuit analytics. Loopio fits firms with heavy multi-sector RFP volume who need one platform across industries. Unanet GrowthStudio is the right evaluation for AEC and GovCon firms already on the Unanet platform. AutogenAI is best evaluated by firms bidding in UK/EU markets or across multiple sectors beyond AEC.

Why generic AI writing tools fall short for AEC

Generic AI tools weren’t built for AEC proposal workflows. They generate from their training data, not your firm’s portfolio, so the tool produces plausible-sounding project experience your firm doesn’t have, rather than surfacing the real credentials you do.

They summarize RFP requirements instead of extracting them verbatim, which in AEC is the difference between a compliant submission and a disqualified one. And they have no connection to the DAM systems, CRMs, and ERPs where your proposal assets actually live. Every pursuit starts with a manual upload problem that the AI can’t solve.

The platforms in this comparison were evaluated specifically because they address one or more of these gaps. The criteria above reflect the same logic.

For a closer look at how AEC teams structure AI into their pursuit workflow, this guide to AI in AEC proposals covers the specifics.

What about building it in-house?

If your firm is already in the Microsoft ecosystem, someone will ask: “We have Copilot and SharePoint, why do we need another tool?” It’s a fair question. Copilot handles simple tasks well: summarizing a past proposal, editing for tone, or drafting a cover letter. What it doesn’t do is verbatim compliance extraction, Go/No-Go scoring, or native DAM integration. 

For teams with low proposal volume and no dedicated proposal manager, starting with Copilot is reasonable. If you’re running a serious pursuit program with complex compliance requirements, purpose-built tools will outrun the DIY path.

FAQs

Which AI proposal tool is best for AEC firms? 

It depends on your technology stack. If you’re running OpenAsset DAM, OpenAsset Shred is the strongest fit. It’s the only platform in this comparison with native DAM integration and verbatim compliance extraction. If you’re evaluating a standalone AEC-native tool, Kantiv leads on pursuit analytics. For multi-sector RFP volume, Loopio has the most review validation. If you’re in the Unanet ecosystem, GrowthStudio is the right conversation to have with your Unanet rep.

How is OpenAsset Shred different from Kantiv (Joist.ai)? 

The main difference is DAM integration. OpenAsset Shred connects natively to OpenAsset DAM, so your project photos, team bios, and past proposals flow directly into proposal development without manual upload per pursuit. Kantiv doesn’t have that connection. 

On the other side, Kantiv’s pursuit analytics are more developed right now: win/loss pattern tracking, historical pursuit data, client relationship context. Both tools are genuinely AEC-native. The right choice comes down to whether you’re on OpenAsset and how central pursuit analytics are to your BD process.

Does OpenAsset Shred support SF330 qualification packages?

Shred can help teams produce SF330 content by surfacing and grounding answers from prior submissions and your content library. This includes content like firm details, project info, resumes, and narratives. However, Shred does not auto-fill SF330 forms or templates. 

Does AI proposal software work with Deltek or Unanet?

It depends on the tool. While OpenAsset Shred does not have any direct integrations aside from OpenAsset DAM and Adobe InDesign, OpenAsset DAM does integrate with Deltek Vision and Vantagepoint,  Unanet CRM, and Procure, allowing an indirect connection when OpenAsset Shred is used with OpenAsset DAM. 

Kantiv lists Salesforce and Adobe InDesign as integrations; no Deltek, Unanet, or Procore integrations appear in Kantiv’s public documentation. Unanet GrowthStudio integrates within the Unanet ecosystem.

Is my firm’s proposal data used to train AI models? 

OpenAsset Shred’s on-record commitment is that customer data is never used to train public AI models, and data is isolated by firm. That’s the most explicit privacy commitment in this comparison. Kantiv, Loopio, and AutogenAI don’t publicly disclose data training policies in their G2 reviews or on their websites. 

Unanet markets a “private AI instance” but that claim doesn’t appear in reviewer language. If your firm has sensitive project data or client confidentiality requirements, OpenAsset Shred’s explicit policy is the clearest answer available in this set.

Conclusion

Winning proposals don’t come from teams that use the most AI. They come from teams that use AI that understands AEC.

Generic tools will get you a first draft fast. They won’t catch a missed compliance requirement, pull the right project photo from your DAM, or tell you whether the pursuit is worth your team’s time. Those are the problems that determine whether you win — and they’re what the tools in this comparison were built to solve.

Choose based on your stack and your firm’s actual pursuit workflow. That’s where the answer lives.

Ready to see how OpenAsset Shred works with your firm’s proposal library?

Sources:

• PR Newswire, June 2025: OpenAsset Shred launch announcement 
• G2 Software Reviews: Loopio, AutogenAI, Kantiv, Unanet GrowthStudio product pages (data pulled May 2026)
• Vendor product pages: Kantiv, Loopio, AutogenAI, Unanet GrowthStudio (reviewed May 2026)