Sep 6, 2026
Here's the dirty secret of AI scoring: the number always looks the same. A "74% fit" renders just as confidently whether it was computed from a deep project portfolio and a successful AI analysis, or from three projects and a forty-word scraped posting. Most tools never tell you which one you're looking at. We think that's the single biggest reason experienced principals don't trust AI scores — and they're right not to.
Every opportunity in your ArchFP discovery feed carries a Fit score from 0 to 100, personal to your firm. It's built from your actual portfolio — the sectors you really build in, learned from your Firm Projects rather than a settings form — and an AI pass separates the look-alikes a keyword match can't: for a school-focused practice, a school beats a transit depot, even when the depot is the bigger job. Sort by Fit and the work you're positioned to win rises to the top, each row carrying a one-line reason.
And if your firm genuinely does two kinds of work — schools and labs, say — the score now reads each opportunity against the right side of your practice, instead of a blurred average of both.
These past few weeks we shipped the layer we think actually matters. Every Fit score now carries a confidence level, computed from the evidence behind it: how many past projects the comparison rests on, how much substance the RFP posting actually had, and whether the deeper AI analysis ran or fell back to basic matching.
When the evidence is thin, the score says so. It renders muted, tagged "est.", and the tooltip tells you exactly why: estimate — based on 2 past projects · short RFP description. A strong score on strong evidence looks like a verdict. A score on thin evidence looks like what it is: an estimate.
A confident-looking number built on thin evidence isn't a small flaw in an AI tool. It's the whole reason experienced people stop trusting them.
Your team's behaviour is the best ground truth there is — what you save, what you pursue, what you win, and what you dismiss. Once your firm has a real track record on the platform, those signals begin to refine the ranking: opportunities similar to the ones you pursue get a nudge up; opportunities similar to the ones you dismissed get a nudge down.
We built this carefully. The behaviour signal doesn't switch on until your team has enough recorded actions to mean something. Dismissing an obvious mismatch teaches the system nothing — but dismissing something that scored well is treated as the valuable correction it is. And the signal refines the score; it never dominates it.
No portfolio yet? No fake number. A brand-new account sees "Add past projects to unlock Fit scoring" — because a fit score with nothing to compare against would be theatre, not signal.
No silent degradation. If the deeper AI pass can't run, you still get the deterministic score — and the confidence drops, with the reason shown. The system never quietly gets worse without telling you.
We hold the score accountable. We track whether high-fit opportunities are actually the ones firms end up pursuing, so the scoring is calibrated against reality — not vibes.
Back in July we wrote about teaching our review AI to say "I'm not sure". This is the same conviction applied to discovery: in an industry where proposals carry real money and real reputations, an AI score you can't interrogate is a liability wearing a badge. One that shows its evidence, admits its limits, and learns from your judgment is something closer to a colleague. That's the bar we're building every ArchFP feature to.
If you'd like to see your firm's own feed ranked — complete with scores that admit what they don't know — book a 15-minute demo and we'll run it on your firm's real portfolio.
Aug 16, 2026
Every RFP asks for it, one way or another: relevant experience, representative projects, a project experience matrix, SF330 Section F. And most firms answer it the same way every time — someone opens two or three old proposals, copies the closest project write-ups into the new document, swaps the client name, updates a square-footage figure they are not totally sure is current, and hopes nothing is stale. The project sheet that took an afternoon to build gets rebuilt, slightly differently, for the next submission. And the one after that.
Relevant experience typically carries 20 to 25 percent of the evaluation score — committees want proof you have done this before, for a client like them. But the raw material lives everywhere and nowhere. A single project's details are scattered across the original proposal, a principal's CV, a reference letter, and the marketing coordinator's layout file. There is no single source of truth, so every proposal reconstructs one from memory, and small errors creep in: an outdated cost, last year's completion date, the wrong gross floor area.
And the same project ends up described five different ways. The version you wrote for a school board emphasised community consultation. The version for a hospital emphasised phased construction around a live, occupied site. Both are accurate. Both are good. And both are buried in PDFs nobody can find when the next relevant RFP lands.
Here is the thing: you have already written excellent descriptions of every project your firm has delivered — many times over. The problem was never a shortage of content. It is that the content is not structured, not deduplicated, and not reusable. And the usual fix — a project database someone maintains by hand — just becomes another spreadsheet that goes stale by the second proposal. The better approach is a system that reads the proposals you have already submitted and assembles the portfolio for you.
It extracts your projects from your own proposals. Point ArchFP at a past submission and it pulls your firm's projects into structured profiles — client, building type, location, gross floor area, floors, cost, completion year, scope, services, certifications, awards, and the team members who worked on each one. It is deliberate about ownership: it captures the projects your firm delivered and skips subconsultant experience and reference projects that belong to other firms, so your portfolio is actually yours.
It merges duplicates instead of stacking them up. The same project shows up in a project sheet, a CV, and a reference list; ArchFP recognises it is one project and combines the details into a single record. Across documents it matches by name and, when the names do not line up — “St. Mary's Elementary” versus “St Mary Elementary School” — by meaning. When it merges, it only fills in blanks; it never overwrites something you have already refined.
It remembers every angle you have described a project from. This is the part that matters most. Each time a project appears in a new proposal, ArchFP keeps that version's description as its own variation, tagged with a one-line summary of what it emphasised. So a single project carries all of its angles at once — the community-engagement version, the phased-construction version, the sustainability version — and when the next RFP calls for one of them, you start from the right one instead of a blank page.
It keeps the details that actually score. Client testimonials tied to the project, owner contact information, delivery method, student or bed counts, sustainability features, awards — the specifics an evaluator rewards — are captured with the project instead of left behind in the source document.
Once the portfolio exists, the rest of ArchFP draws on it. Your AI-drafted responses, your Go/No-Go analysis, and the Ask ArchFP assistant all pull from the same project records, and you can shortlist the right projects straight onto a proposal. The portfolio is not a folder you visit; it is the memory the whole workspace works from.
Your project history is one of your firm's most valuable assets, and for most firms it is also the most disorganised. Every proposal you have ever submitted was a deposit into a portfolio you were never quite able to withdraw from. Firm Projects turns that back-catalogue into a structured, searchable, current record — so the section evaluators weigh most, and firms dread most, is ready before the next RFP is even posted.
If your project sheets get rebuilt from scratch every time and quietly drift out of date in between, book a 15-minute demo and we will build a portfolio from a few of your own past proposals — so you can see what has been hiding in them all along.
Jul 24, 2026
If your firm has submitted forty proposals, the fortieth should be dramatically easier than the first. You've answered the sustainability question before. You've described your QA process before. You know why you lost the last three school board bids. In practice, most firms' fortieth proposal is about as hard as their first — because almost none of what they learned survived the submit button.
Two things disappear every time a proposal goes out the door, and most firms never notice either one.
The first is the writing. A single proposal holds dozens of carefully worded answers — your approach to stakeholder engagement, your accessibility narrative, your firm's story — and the moment it's submitted, all of it gets zipped into a PDF and filed in a folder nobody opens again. We've written before that 60 to 70 percent of proposal content is reusable across submissions. The problem was never that the good answers don't exist. It's that they aren't findable when you need them.
The second is the outcome. When a firm wins, nobody records which answers were in the winning submission. When a firm loses, nobody records why. The proposal is finished, everyone moves on to the next deadline, and the single most useful piece of information — did this actually work? — evaporates. In enterprise sales, win/loss analysis is a standard discipline. In AEC it rarely happens, because there's never been a place to put the answer.
The firms that pull ahead aren't writing better answers than everyone else. They're keeping them. Every proposal should deposit something reusable into a library that gets richer over time, and every outcome — won or lost — should teach the system what to reach for next. That's a flywheel: the more you use it, the better it gets, and the harder it becomes to go back to starting from a blank page.
The hard part isn't generating answers. It's making sure the answer you write today is still findable a year from now, when a new RFP asks almost the same question and nobody can remember which proposal it lived in.
Win/loss capture on every submitted RFP. Once a proposal is submitted, you can mark it Won or Lost right from the builder — on the list card or in the detail header. Recording the status takes one click and never forces you through anything else.
Winning promotes your best answers. When you mark a proposal Won, ArchFP takes the answers you shortlisted for it, tags them as part of a winning submission, and bumps them so they surface first the next time a similar requirement comes up. If it's a project you want in your portfolio, you can turn it into a Firm Project in the same step.
Losing turns into data, not a shrug. Mark a proposal Lost and ArchFP captures why — a structured reason and an optional debrief note — so the pattern behind your losses becomes something you can actually see. All of it is optional; recording the outcome is never blocked by the details.
Every AI draft is captured the moment it's written. When the AI drafts an answer for you, it's now indexed and searchable immediately — findable by semantic match, by the auto-fill on your next RFP, and by the Ask ArchFP assistant. The answer you generate for today's proposal is already working for the next one. The Answer Library separates Drafts from Active with one-click Approve, and a review panel appears right after generation so nothing sits in limbo.
And if you forget, ArchFP asks. About three weeks after a deadline passes, a short “Did you win?” nudge lands in your inbox with one-click Won and Lost buttons — so the outcome gets captured even when the proposal is already three projects behind you.
Every AI proposal tool can generate a first draft. Far fewer make that draft worth something the second time. The value of ArchFP isn't any single answer it writes — it's that your firm's library, your winning language, and your loss patterns compound into an advantage that a blank document and a shared drive never will. Proposal number forty should start from a much stronger place than proposal number one. Now it does.
If your firm's best proposal writing keeps disappearing into folders nobody opens, book a 15-minute demo and we'll show you what a compounding library looks like on your own past submissions.
Jul 2, 2026
Here's an uncomfortable truth about AI proposal tools, ours included: a reviewer that is confidently wrong is worse than no reviewer at all. If a compliance check tells you a mandatory requirement is missing from your submission when it's actually sitting on page 34, your team burns an evening rewriting content that already exists. And if it tells you something passes when it doesn't, you find out from the selection committee.
When we dug into the cases where our own Submission Review missed the mark, two patterns kept showing up. The first is language equivalence: the RFP asks for “10 years of experience,” the firm wrote “over a decade,” and a literal-minded check calls that a miss. The second is silence about uncertainty. Most AI tools return a verdict — pass or fail — with no signal for how sure the model actually is. Every answer looks equally confident, so you can't tell which ones deserve a second look.
We think the bar for AI in proposal work should match the bar for a junior staff member doing the same job: show your work, flag what you're unsure about, and never present a guess as a fact. That standard shaped everything in this release.
Confidence scores on every verdict. Each requirement in Submission Review now carries the AI's self-rated confidence, displayed as a chip next to the verdict. High means explicit, direct evidence. Low means look at this one yourself. And there's a hard rule underneath: if the AI wants to mark a requirement as failed but its confidence is low, it must downgrade to “partial” and explain what would resolve the ambiguity — instead of quietly guessing against you.
Click a verdict to see the source. Every requirement now has a View Source button that opens your own submission PDF in a side panel, jumps to the relevant page, and highlights the passage the AI is citing. Agree or disagree with the verdict in one click — no more downloading your own proposal and hunting with Ctrl-F.
Equivalence rules. The reviewer now explicitly bridges paraphrase: a decade equals ten years, OBC 2024 equals the Ontario Building Code 2024 edition, and a capability stated in any submission document counts regardless of which document the requirement came from.
Honest failure states. If part of a review can't be completed — a processing error, a timeout — those requirements are now labelled “not evaluated” with a one-click re-evaluate button, instead of being disguised as fails. And if you change your submission documents after running a review, a banner tells you the results may be stale.
The AEC industry is right to be skeptical of AI that can't be audited. Proposals carry real money and real reputations, and “the tool said so” is not a defence a principal can take to a selection committee. Verifiability isn't a nice-to-have feature — it's the price of admission for AI in this industry. This release is us paying it.
If you want to see what a verifiable AI review looks like on one of your own submissions, book a 15-minute demo.
Jun 18, 2026
A decade ago a public-sector RFP for a mid-sized institutional project ran 40 to 80 pages. Today, the same procurement comes in at 150 to 250, and we regularly see school board, hospital, and municipal packages cross 400. Addenda, evaluation matrices, appendices, sub-consultant forms, sustainability and DEI questionnaires — each one adds weight, and almost none of it gets shorter the following year.
Procurement teams add language; they almost never remove it. Every audit finding, every legal challenge, every project that went sideways gets translated into a new clause for the next RFP. Public-sector compliance frameworks compound. Sustainability requirements that didn't exist five years ago now occupy 20-page appendices. Indigenous consultation, accessibility, supply-chain provenance — all of these are new sections that are now standard.
Here's what nobody talks about: most teams (and most AI tools) handling these RFPs silently truncate. A 300-page document gets fed into a tool with a fixed context window, the tail is dropped, and the user gets a confident-looking checklist that quietly omits the last forty pages — which is exactly where submission forms, scoring rubrics, and declarations tend to live.
The result isn't dramatic. It's a missed mandatory form, an unchecked compliance box, a scoring penalty. The kind of thing that loses you the proposal without you ever knowing why.
For very large RFPs, two things have to be true. First, the tool should let you decide what's worth extracting before it spends time on everything — because some sections (Evaluation Criteria, Submission Requirements, Forms & Declarations) are disproportionately critical and worth focused attention. Second, when you do extract everything, the document has to be processed in full — chunked if necessary, but never silently dropped.
This week we added two things to address exactly this. A new requirement category pre-scan runs in seconds and shows you a table of contents of what's actually in the RFP — so you can target your extraction at Submission Requirements and Evaluation Criteria before committing to a full pass. And a new chunked extraction path for very large documents handles RFPs up to roughly 700 pages without dropping the tail. If a section gets skipped, you see it.
If your firm regularly responds to large public-sector RFPs and you'd like to see how this works on a real document, book a 15-minute demo.
May 3, 2026
Most firms calculate the cost of losing an RFP by asking what the project would have been worth. That's the wrong math. The real cost is on the input side, and it's bigger than people think.
Research from Tenders Resource Centre and OciWins puts the production cost of a single mid-complexity proposal at $12,000 to $15,000, with firms typically spending 2 to 6 percent of total contract value on proposal preparation alone. Most of that is senior staff time: architects bill at $125 to $250 per hour, and a typical RFP response takes 40 to 100 hours across the team.
According to Deltek's research on architecture firm KPIs, the typical net multiplier in an A&E firm is 2.94 to 3.54x. That's how firms recover overhead from direct labour. The practical implication: every 100 hours spent on a losing proposal requires 300 to 350 billable hours to recover the overhead impact. That's not "the fee you missed." That's billable work that has to make up the gap.
Those 40 to 100 hours came from somewhere. Usually a senior associate who could have been doing schematic design, or a principal who could have been in client meetings. The 2023 median utilisation rate for architecture firms is 61 percent. Part of that gap is senior staff tied up on proposals that the firm was never going to win.
If your firm submits 25 RFPs a year at a 40% win rate, that's 15 losing proposals. At 60 hours each, that's 900 hours of senior staff time spent on proposals that produced nothing. Apply the net multiplier and you're looking at 2,700+ billable hours of recovery work — most of a full-time equivalent's annual capacity.
Tightening Go/No-Go criteria isn't about pursuing fewer opportunities. It's about not paying $12,000-plus for proposals you were never going to win.
This is what ArchFP's Go/No-Go evaluation is built around. It scores each opportunity against your firm's actual eligibility and strategic fit before you commit a principal's week to it. If your firm wants to spend its proposal hours where they're more likely to win, book a 15-minute demo and we'll show you what a data-driven pursuit process looks like.
Apr 26, 2026
Most architecture firms write proposals without a clear picture of how the scoring actually works. The committee that decides whether you win is using a structured rubric, and the way they apply it has predictable patterns most firms don't account for.
Public-sector RFPs use weighted evaluation criteria that must be disclosed in the RFP itself. Research from Responsive, Arphie, and Inventive on RFP scoring shows the typical weight breakdown for AEC proposals:
In Canada and the US, federal architectural services often follow Qualifications-Based Selection under the Brooks Act, where price is excluded from the initial evaluation. Qualifications carry the entire weight until a shortlist is chosen, then fee is negotiated separately. This is why a low fee proposal rarely wins a federal project.
A few patterns from research on proposal evaluation bias and cognitive load are worth knowing:
If your proposal forces the evaluator to hunt for the answer, you lose points even if the answer is there. The committee scoring your submission has a finite amount of attention, and they're scoring under time pressure with five other proposals on the desk.
The firms that score best aren't the ones with the most content. They're the ones that map every section of their proposal to a specific evaluation criterion, lead with the strongest material, and make it impossible for the evaluator to miss the points you're earning.
This is what ArchFP's submission review feature is built around. It scores your draft against the RFP's actual evaluation criteria the same way a committee would, flags sections where you're losing points, and identifies where one stronger paragraph would lift your overall score.
If your firm wants to know how a committee would score your next submission before you send it, book a 15-minute demo and we'll walk you through it.
Apr 19, 2026
In most architecture and engineering RFP evaluations, the Project Understanding section is where evaluators form their first impression. Research by Arphie on proposal evaluation found that once an evaluator forms that impression, they "unconsciously seek evidence supporting that judgment while discounting contradictory information."
Technical approach is the heaviest-weighted category in most AEC proposal scoring, typically 25 to 40 percent of the total. Project Understanding is where your technical narrative starts, so it shapes how evaluators read everything that follows.
Research by ContraVault AI on AEC proposal mistakes identifies generic content as a top reason firms lose points. The Project Understanding section is particularly vulnerable because it's often written last, under time pressure, and pulled from a similar past proposal. MarketLink AEC's analysis of proposal templates pegs the sweet spot at roughly 85 percent tailored content. Anything more generic reads like boilerplate to a committee that has already seen nine submissions.
A strong Project Understanding section covers four things:
This is one of the sections ArchFP's AI drafting handles differently. Instead of pulling from a generic template, it drafts the Project Understanding using the specific requirements from the current RFP, relevant past projects from your portfolio, and your firm's own writing style. The first draft arrives connected to the source document, not detached from it.
If your Project Understanding sections read the same across every submission, book a 15-minute demo and we'll show you how to keep each one specific without starting from scratch.
Apr 12, 2026
According to procurement research tracked by VisibleThread and others, roughly 4% of proposals are still disqualified for failing to include required documents or sections. That number used to be closer to 15%. It's come down, but it still means firms are losing opportunities to errors that have nothing to do with the quality of their work.
The most common reasons are not surprising: missing a mandatory form, using the wrong client name from a copy-paste, leaving outdated project details in a section pulled from a previous submission, or not addressing a specific evaluation criterion that the committee is scoring against.
Evaluation committees score proposals against specific criteria, often with disclosed weights (for example, 40% technical approach, 30% relevant experience, 20% team qualifications, 10% fee). A study by Inventive AI and Hudson Bid Writers found that firms frequently spend equal time on every section instead of weighting their effort toward the highest-scored criteria. The result is a proposal that "checks the boxes" but doesn't score well where it matters most.
Procore's research on common RFP mistakes found that many proposals stop short of explaining why the team is the best choice for the project, missing the chance to connect their specific experience to what the evaluator is actually looking for.
According to Zweig Group's research on QA practices in architecture firms, fewer than half of firms that claim to have a quality review process actually use it. Proposals are typically finished under time pressure, reviewed briefly by whoever is available, and submitted. The structured, criteria-by-criteria review that would catch most of these errors rarely happens because there isn't time.
This is what we built the submission review feature in ArchFP to solve. Upload your draft proposal alongside the RFP documents, and the system scores your response against each evaluation criterion, flags missing requirements, identifies gaps where you could score higher, and estimates how an evaluation committee would rate your submission. It takes a few minutes instead of the hour-long review that nobody has time for.
If your firm's final review process is a quick skim before the deadline, book a 15-minute demo and we'll show you what a structured pre-submission check looks like.
Apr 3, 2026
Pull up your firm's last five proposals. How many times did you rewrite essentially the same paragraph about your design approach or your experience with sustainable buildings? If you're like most firms — every single time.
A firm submitting 25 RFPs per year at ~22 hours each generates hundreds of pages of polished content. And almost none of it gets reused effectively. Instead, each proposal starts with someone opening the last similar submission, copying chunks into a new document, and spending hours rewriting content that's 60-70% identical to what already exists.
The shared drive with 200 proposal folders isn't a system. It's a graveyard of good writing that nobody can find when they need it.
If 60% of your proposal content is reusable, that's roughly 330 hours per year spent rewriting answers that already exist somewhere in a shared drive. At a principal's billing rate, that's real revenue walking out the door — and it doesn't even account for the inconsistency when four different people write four different versions of your firm's story across concurrent RFPs.
Firms that win consistently aren't writing better answers. They're writing them once, refining them, and reusing them strategically — through a searchable library of categorised answer snippets, project profiles, and team qualifications that's ready to adapt for each new submission.
This is one of the core problems we built ArchFP to solve. Upload past proposals and our AI extracts your best answers into a searchable library. When a new RFP lands, it drafts responses using your firm's own content and writing style. Each proposal builds on the last instead of starting over.
If your firm is still rewriting the same answers from scratch, book a 15-minute demo and we'll show you what your library could look like.
Mar 22, 2026
Every architecture firm knows the feeling. An RFP drops with a tight deadline, and within hours you're scrambling to assemble a team — structural, mechanical, electrical, civil, landscape, maybe a specialist or two. You reach out to the firms you've worked with before, hope they're available, and paste their credentials into your submission.
It works. Until it doesn't.
Most firms pick subconsultants the same way every time: the principal or project manager pulls from a mental shortlist of "people we've worked with." There's rarely a structured record of which subconsultants were teamed on which proposals, what they cost, or how the project turned out.
This creates three problems that directly affect your win rate:
1. You default to the same partners regardless of fit.
When time is short, you go with who you know. But the structural engineer who was perfect for your last healthcare project may not be the right fit for a K-12 school with a tight budget. Evaluation committees notice when your subconsultant team doesn't match the project scope — it signals that you assembled the team quickly rather than strategically.
2. You lose institutional knowledge when people leave.
If the associate who manages your subconsultant relationships leaves the firm, those relationships — and the context around them — walk out the door. Who did we use for the Halton school board project? What did the MEP consultant charge last time? Were they responsive during construction administration? That knowledge evaporates.
3. You can't demonstrate teaming track record.
Some RFPs explicitly ask for evidence that your proposed team has worked together before. If you can't quickly show which past projects involved the same subconsultant lineup, you're leaving points on the table. Evaluation committees value teams that have a demonstrated working relationship — it reduces their risk.
When a selection committee reviews your subconsultant page, they're looking for three things: relevance (does this firm have experience with this project type?), capacity (can they actually take this on?), and chemistry (has this team delivered together before?).
The firms that win consistently aren't necessarily teaming with the most prestigious subconsultants. They're teaming with the right ones for each specific opportunity, and they can prove it with project history.
The fix isn't complicated, but it does require moving beyond spreadsheets and memory. Firms need:
We've been building these capabilities into ArchFP — from a searchable partner directory and proposal shortlisting to automatic CV extraction and an AI assistant that can answer questions like "which structural engineers have we teamed with on school projects?" using your firm's actual data.
If your firm's teaming decisions are still driven by who the principal remembers from the last project, book a quick demo and we'll show you what a data-driven approach looks like.
Mar 8, 2026
The average architecture firm spends 20 to 40 hours on a single RFP response. For smaller firms — 5 to 50 people — that's a principal or senior associate buried in proposal work instead of doing what they were hired to do: design.
And after all that effort, most firms win less than 30% of the proposals they submit. That means 70% of those hours produce nothing. No project. No revenue. Just a PDF that gets ranked third and filed away.
We've spent the past year talking to architecture firms across Ontario and the broader AEC industry about how they handle proposals. The patterns are remarkably consistent, regardless of firm size or specialization.
1. They miss the deadline — or never see the opportunity.
RFPs are posted across dozens of procurement sites — MERX, Biddingo, SAM.gov, municipal portals, provincial platforms. Most firms rely on one person checking one or two sites manually. Opportunities slip through, or they're discovered too late to submit a competitive response.
2. They start from scratch every time.
Architecture firms do similar work across projects — healthcare, education, municipal, residential. But when a new RFP lands, the response gets written from a blank page. Past proposals live in scattered folders, old Word docs, or a senior associate's memory. There's no system for reusing what worked before.
3. The response doesn't match the evaluation criteria.
RFP evaluation committees score against specific criteria — relevant experience, team qualifications, project approach, fee structure. Firms that bury their strongest points under generic boilerplate lose to firms that map every section to what the evaluator is actually scoring. It's not about who's the best architect. It's about who answers the question the evaluator is asking.
4. They pursue the wrong opportunities.
Not every RFP is worth chasing. If the scope doesn't match your expertise, the insurance requirements exceed your coverage, or the client already has a preferred firm, you're spending 30 hours on a submission you were never going to win. Most firms don't have a structured Go/No-Go process — they chase everything and spread themselves thin.
5. The proposal doesn't sound like the firm.
When proposals are rushed, they default to generic language. The firm's voice, its design philosophy, its unique approach to projects — all of that gets lost. Evaluation committees read dozens of submissions. The ones that stand out are the ones that feel intentional, specific, and authentic to the firm submitting them.
The solution isn't hiring more people to write proposals. It's eliminating the repetitive work that consumes most of the 20-40 hours:
This is what we built ArchFP to do. Not to replace the human judgment that wins projects, but to free up the time and mental bandwidth that your team needs to bring that judgment to every proposal.
We're currently in closed beta with architecture firms across Canada and the US. If your firm is spending too many hours on proposals and winning too few, book a 15-minute demo and see if ArchFP is a fit.
Mar 5, 2026
We've tightened the connection between evaluating an opportunity and building your proposal. Go/No-Go analysis now flows directly into your proposal workspace — fewer clicks, less context-switching, and no need to re-upload documents between stages.
This is part of a broader effort to make the entire RFP lifecycle feel like one continuous workflow instead of disconnected steps.
Mar 1, 2026
We're live. ArchFP is now available in closed beta for architecture firms across Canada and the US.
We built ArchFP to tackle a specific problem: architecture firms spend 40+ hours on every proposal, most of it on repetitive work that doesn't require design expertise. ArchFP handles the grind — from finding the right opportunities to assembling a polished submission — so your team can focus on strategy and design.
This is just the beginning. We're shipping fast and listening closely. If you have feedback, we want to hear it. Book a demo to see what we've built.