Proposal Intelligence
Platform
A comprehensive vision for what Connected is building – across proposal intelligence, digital asset management, client-facing proposals, Salesforce integration, and the legal framework to protect it all. Informed by the Discovery Service Matrix, the Connected Proposal Playbook, and the OpenAsset competitive context.
What we are building and why
OpenAsset is a purpose-built AEC SaaS platform that does two things: a centralised digital asset library – project photos, capability statements, whitepapers, client quotes, team references and testimonials, all searchable and tagged – and an AI-powered proposal module that ingests RFPs, runs go/no-go analysis, and assists with content assembly. It is, in essence, the infrastructure layer that would sit under everything Connected is building across AU and the US.
We should not buy it. We should build our own. The difference is what gets baked in. OpenAsset is a generic AEC tool. What Connected builds will have our ECI methodology, our sector verticals, our Playbook, our IP, and our data embedded at the foundation. That is not a feature difference – it is a structural competitive advantage that a SaaS subscription can never replicate.
The Connected Proposal Intelligence Platform is the internal system that makes Connected faster, more consistent, and more strategically rigorous in how it pursues and wins work. It starts with the discovery proposal generator – built and ready for deployment pending API configuration – and builds toward a full platform that spans proposal intelligence, digital asset management, client-facing proposal delivery, Salesforce integration, and AU/US operational split views.
Every layer of the platform compounds on the last. The data generated by proposals informs the asset library. The asset library feeds the proposal assembly engine. The proposal assembly engine powers the client-facing delivery layer. The analytics from that layer feed back into win strategy. Built correctly, this becomes a system that gets sharper with every bid Connected runs through it – and that is the version competitors cannot buy.
The four-layer platform
The platform is built in four layers, each extending the last. The first is built and ready to deploy. The rest are the roadmap.
What it does now
The discovery proposal generator is the Layer 1 tool. It is purpose-built around Connected’s discovery methodology and Playbook. The interface is complete – deployment requires an Anthropic API key, a server-side proxy function to handle API requests securely without exposing credentials in the browser, and an access token to gate the site. Once configured, it is accessible to the full team from a URL.
Foundation. Building a rigorous picture of the current state, people, and operational requirements before design thinking begins. Applicable across all six sectors.
Options. Stress-testing the opportunity across property, location, funding, and scale. Not all services apply to every sector – the platform surfaces relevant ones based on sector selected.
De-risking. Change readiness, business continuity, sustainability, redundancy, and business case – ensuring the project is structurally sound before design begins.
Master prompt architecture
The platform’s AI output is determined by its master prompts – structured instructions drawn directly from the Connected Proposal Playbook. The Playbook defines a six-stage bid framework and ten AI prompt modules. The platform operationalises these in a structured interface so consultants don’t construct them manually.
Go/No-Go, Kick-Off, Win Strategy, Proposal Build, AI Prompts, Pre-Submission. The platform currently operationalises the AI Prompt stage (Stage 5) for discovery proposals. The full six-stage digital workflow is the Layer 2 and 3 build.
The Playbook defines the AI’s role precisely. It acts simultaneously as four perspectives: the client’s CEO – outcomes, risk, and organisational consequences of getting this wrong; the client’s Head of Procurement – evaluation criteria, value for money, commercial risk; a bid director with 20 years winning complex capital works tenders in life sciences, healthcare, and laboratory environments; and a construction specialist who understands what actually goes wrong on projects like this.
The job of the AI is not to make Connected sound good. Its job is to tell Connected what they need to hear to win – and what they need to avoid to not lose. Every response must be specific to this project, this client, this environment. No construction cliches. No generic statements any contractor could make.
The Playbook specifies eight inputs. Quality of inputs determines quality of outputs. The platform pre-loads these from the project context form.
AI cannot replace your relationships and your intimate knowledge of a client and their project specifics. This model and approach is a support, not a solution. Every output must be thoroughly reviewed. The platform’s job is to eliminate the blank-page problem, enforce structural discipline, and surface intelligence the team might miss under time pressure – not to substitute for the human judgment that wins work.
Client-facing proposals and engagement analytics
Layer 4 of the platform introduces a client-facing proposal delivery layer – proposals sent as interactive, tracked web documents rather than static PDFs. This turns every proposal submission into an intelligence-gathering exercise.
Instead of sending a PDF that disappears into a client’s inbox with no signal of what happens next, Connected sends a secure, branded proposal link. The client reads it in their browser. Connected sees exactly what they read, how long they spent on each section, what they skipped, what they returned to, and who they forwarded it to. That intelligence feeds directly back into the follow-up conversation – and over time, into win strategy.
Client-facing proposal analytics can be implemented via purpose-built tools (Qwilr, Proposify, Pandadoc – all offer section-level analytics and viewer tracking) or built natively as part of the Connected platform. The native build is the right long-term answer – it keeps the data inside Connected’s systems, integrates directly with Salesforce, and allows the analytics to feed back into the AI prompt layer. The SaaS tool approach is faster to deploy and appropriate for the Layer 4 phase while the native build is scoped.
Note: client-facing proposal links require careful handling – see Section 08 on legal and data obligations before deploying tracking to any recipient.
Salesforce integration
Salesforce is the data backbone of the platform. Every piece of client intelligence, opportunity data, and proposal outcome that Connected captures should live in Salesforce and be accessible to the platform. The integration makes the platform smarter with every engagement.
The platform should never ask a consultant for information that Salesforce already has. Client name, sector, project history, key contacts, and prior engagement notes should pre-populate the proposal form from the CRM record. Conversely, everything the platform generates – proposal content, win/loss outcomes, client engagement data – should write back to Salesforce automatically. The goal is a single source of truth that gets richer with every bid.
Client quotes and testimonials are among the highest-value assets in any proposal, yet they are consistently the hardest to find under time pressure. The DAM treats them as first-class assets, stored and tagged with the same rigour as project photography or capability statements.
Each quote or testimonial is tagged to: the client who provided it, the project it relates to, the sector and environment type, the specific outcome or capability it evidences, and the team member or role it references. When the proposal assembly engine runs a prompt against a new opportunity, it queries these tags to surface the most relevant quote or reference automatically – a healthcare client quote for a healthcare proposal, an operational continuity testimonial for a live environment bid.
Referee contacts are stored as a separate asset type linked to both the client record and the project record in Salesforce. When a tender requires nominated referees, the platform surfaces the relevant contacts based on project similarity – no more hunting through emails or relying on memory for who gave a good reference on which project. This alone is worth building the DAM for.
| Integration point | Direction | What it enables | Build phase |
|---|---|---|---|
| Opportunity record pre-population | Salesforce to platform | Client and project details auto-fill the proposal form. No re-entry of data already in CRM. | Layer 2 |
| Contact and decision-maker profiles | Salesforce to platform | Key contact intelligence informs the AI’s client decision driver analysis. | Layer 2 |
| Proposal content write-back | Platform to Salesforce | Generated proposal narratives and selected services recorded against the Opportunity. | Layer 2 |
| Win/loss outcome recording | Platform to Salesforce | Bid outcomes recorded and linked to proposal content – enabling win/loss pattern analysis over time. | Layer 3 |
| DAM project record linkage | Bidirectional | Assets tagged to Salesforce project records, including client quotes, testimonials, referee contacts, and team references. Proposal assembly engine queries project data to pull relevant case studies and supporting evidence. | Layer 3 |
| Client proposal engagement analytics | Platform to Salesforce | Heatmap data, viewer tracking, and re-read signals written to the Opportunity record for follow-up context. | Layer 4 |
| HubSpot sync | Bidirectional | Marketing and business development data from HubSpot synchronised to Salesforce for unified client view. | Layer 4 |
| Mailchimp integration | Platform to Mailchimp | Automated client-facing reports triggered by project phase milestones. When a project moves through a defined stage in Salesforce, a consolidated report is automatically generated and dispatched to the nominated client contacts via Mailchimp. See below for detail. | Layer 4 |
| AU/US regional split views | Salesforce configuration | Region-specific Opportunity and Account data with unified leadership reporting layer. | Layer 4 |
Connected’s Mailchimp account connects to the platform as a client communications layer. When a project moves through a defined milestone in Salesforce – for example, Phase 1 discovery complete, Phase 2 options report issued, or Phase 3 validated brief signed off – the integration automatically compiles a consolidated project report and dispatches it to the nominated client contacts.
The report is generated from the project data already in the platform: services completed in that phase, key findings and outputs, next phase scope, and any relevant assets from the DAM. It is branded, consistent, and arrives without the consultant having to manually prepare a client update under project pressure. The trigger is the phase milestone in Salesforce, not a manual send.
This serves two purposes simultaneously. For the client it is a professional, timely, and informative touchpoint that reinforces Connected’s delivery standards. For Connected it is a data source – Mailchimp’s open and engagement data feeds back to Salesforce, showing which clients are actively engaged with the project narrative and which are not. A client who has not opened a Phase 2 options report before the Phase 3 kick-off is a relationship risk that the platform surfaces before it becomes a delivery problem.
What this achieves
Legal and data obligations
The following is a summary of legal areas that require professional advice before the platform is deployed in client-facing or data-intensive modes. This document does not constitute legal advice. Connected should engage an IT and commercial lawyer with experience in Australian privacy law, US data regulations, and AI/SaaS contracting before proceeding with Layers 3 and 4. The areas below define the scope of advice required.
Return on investment — cost vs time saved
The platform’s running cost is negligible. The time it saves is not. This section makes the financial case for building rather than waiting, and for prioritising deployment over further scoping.
A senior consultant’s time is one of Connected’s most valuable and finite resources. A discovery proposal currently takes an estimated 2-4 hours of senior consultant time to write from scratch — time spent on drafting rather than strategy, relationships, or delivery. At a realistic volume of 2-4 proposals per month, that is 4-16 hours of senior time every month consumed by writing rather than winning. The platform produces an equivalent first draft in under two minutes at an API cost of roughly $0.02. Regardless of what that consultant time is worth in dollar terms, the platform pays for itself on the first proposal it generates.
| Proposals per month | Senior time currently spent | Platform cost | Senior time saved per month | Senior time saved per year |
|---|---|---|---|---|
| 2 | ~4-8 hrs | <$1 | ~4-8 hrs | ~50-90 hrs |
| 3 | ~6-12 hrs | <$1 | ~6-12 hrs | ~70-140 hrs |
| 4 (max) | ~8-16 hrs | <$1 | ~8-16 hrs | ~95-190 hrs |
The table above assumes 2-4 hours per proposal — a reasonable estimate for a narrative written from scratch. The real figure is likely higher. Proposal writing typically pulls a senior consultant away from billable or client-facing work. It is rarely done in one sitting — meetings, interruptions, and review cycles add time that is hard to track but real. A more honest estimate puts the total time cost at 3-5 hours once coordination and review rounds are included.
At maximum volume — 4 proposals per month — the platform saves an estimated 8-16 senior consultant hours per month. That is one to two full working days of senior capacity returned to the team every month, every month, at a platform cost of under a dollar. Apply Connected’s own view of what that time is worth, and the ROI case writes itself.
| Vercel hosting | ~$20/mo |
| Anthropic API (25 proposals) | ~$15/mo |
| Cloudinary (DAM storage) | ~$50/mo |
| Domain and SSL | ~$5/mo |
| Total platform cost | ~$90/mo |
| Annual platform cost | ~$1,080/yr |
| OpenAsset annual licence | ~$20,000/yr |
| No proprietary methodology | Zero IP value |
| No ECI logic or Playbook | Generic AEC tool |
| No AU/US split view | Not built for scale |
| vs Connected platform | ~$1,080/yr |
| Annual cost difference | $18,920 saved |
Running cost of the full platform: approximately $1,080 per year. Senior time saved at maximum volume — 4 proposals per month — approximately 95-190 hours per year — roughly 2-5 working weeks of senior capacity returned to the team annually. Annual cost saving vs buying OpenAsset: approximately $18,920. Apply Connected’s own view of what a senior consultant hour is worth, and the ROI case is unambiguous.
These figures use conservative assumptions on time and do not account for the win rate improvement that comes from more rigorous, more tailored proposals. That is the real return on investment and the figure that cannot be easily quantified but is the most important one. A single additional ECI award attributed to a sharper proposal covers the platform’s entire annual running cost many times over.
The case for building is not marginal. The platform pays for itself on the first proposal it generates. Everything after that is recovered senior capacity, compounding IP, and a widening gap between Connected and competitors still writing from a blank page.
Risks and mitigations
Immediate next steps
- 1. Obtain an Anthropic API key from console.anthropic.com
- 2. Deploy the site to a hosting provider of choice and configure two environment variables on the server – API key and access token
- 3. Share the URL and access code with the team
- 4. Brief the team on what the tool does, what it does not do, and how to review the output – include the Playbook’s own guidance that AI is a support, not a solution
- 5. Collect feedback from the first ten proposals generated and use it to refine the master prompts
- Sector-specific prompt variants – cleanroom, data centre, food manufacturing, healthcare. The current master prompt produces strong general output; sector-specific variants will materially improve quality for specialist pursuits
- Salesforce integration scoping – map the Opportunity record fields to the proposal form inputs. Define what writes back to Salesforce and when. This shapes all subsequent layers
- Digital asset library architecture – define the tagging taxonomy before building. Asset types include: project photos, capability statements, case studies, client quotes, testimonials, referee contacts, team profiles, whitepapers, and award citations. Tags should map to Salesforce project record fields – sector, environment type, scale, client – so assets link to projects automatically and surface at the right moment in proposal assembly
- Word document output – branded .docx output so the generated narrative drops directly into the Connected proposal template without copy-paste
- Mailchimp connection scoping – map the project phase milestones in Salesforce that will trigger automated client reports. Define the report template structure and the recipient logic before the integration is built. This shapes how client contacts are stored and tagged in Salesforce from Layer 2 onwards
- Procore schema requirement — action required now – Procore holds Connected’s post-award project execution data: programme milestones, site photos, RFIs, and subcontractor records. The full Procore integration is a Layer 3/4 build, but a
Procore_Project_IDfield must be added to the Salesforce Opportunity object before Layer 2 ships. Without it, the link between the proposal record and the live project cannot be made at award — and the harvest loop (site photos into DAM, milestone triggers to Mailchimp, actual vs planned programme back into AI context) cannot close. One field, added now, unlocks the entire delivery intelligence layer later
- Engage an IT and commercial lawyer with Australian privacy law experience to review client tracking, AI processing obligations, and IP protection strategy before any client-facing features are deployed
- Review all active client NDAs for AI processing restrictions before uploading client documents to the platform
- Obtain Anthropic’s data processing agreement and assess against Connected’s client confidentiality obligations
- Update Connected’s standard engagement terms to include AI processing disclosure and IP assignment clauses covering platform-generated content
- Confirm Salesforce data residency configuration for AU and US operations before the DAM and proposal assembly layers go live
The longer-term vision – recording win and loss outcomes, feeding project history back into context, connecting proposal engagement analytics to Salesforce, and building a client-facing delivery layer – positions this as a strategic asset rather than a productivity tool. OpenAsset costs money and gives Connected nothing proprietary. What we build compounds with every bid, every project, and every client engagement Connected runs through it.
The platform that improves with use is the one competitors cannot buy.
Process maps — before and after
Four BPMN-style process diagrams showing how the platform changes Connected’s proposal and BD workflows — from the current manual state through to the full platform operating model across AU and US.
Tech stack — full platform
The platform is built entirely on infrastructure Connected already owns or can access at low cost. No new enterprise contracts. No vendor lock-in. Every layer is replaceable and independently deployable.
| Tool | Purpose | Layer | Cost | Already have? |
|---|---|---|---|---|
| Vercel | Hosting + serverless functions for all tools | L1–4 | Free → ~$20/mo | No — 5 min setup |
| Anthropic API | Claude AI for proposals, tagging, assembly | L1–3 | ~$20–80/mo usage | No — API key needed |
| Cloudinary | Asset file storage, CDN, image resizing | L2–4 | Free → ~$50/mo | No — free tier sufficient |
| Salesforce | Asset metadata, project links, opportunity data | L2–4 | Already paying | Yes |
| HubSpot | Contact sync, BD intel, US market | L4 | Already paying | Yes |
| Mailchimp | Automated client reports, SF-triggered | L4 | Already paying | Yes |
| Procore | Project execution data, milestones, site photos, programme | L3–4 | Already paying | Yes — add Procore_Project_ID to SF now |
| OpenAsset (benchmark) | What we’re replacing / not buying | — | ~$20,000/yr | No — and not buying |
At full operating scale across all four layers: ~$1,500/yr in platform costs (Vercel, Cloudinary, API usage) plus tooling Connected already pays for. OpenAsset runs ~$20,000/yr and gives Connected a generic AEC SaaS tool with no proprietary methodology, no ECI logic, and no AU/US operational split. The cost difference is not the main argument — the IP difference is.
End-to-end workflow
How a connected workflow runs across all four platform layers — from the moment a brief lands to post-award asset capture. Every step either currently exists, is in active build, or is on the near-term roadmap.
- Hunting for assets across shared drives and inboxes — replaced by a DAM search that takes seconds
- Starting every proposal from a blank page — replaced by AI-generated narrative in under two minutes
- Inconsistent go/no-go decisions — replaced by a scored Playbook checklist recorded against the Salesforce opportunity
- Win/loss data that disappears after debrief — replaced by structured logging that feeds back into future proposals
- Every asset uploaded enriches the library — proposals get better assets over time automatically
- Every win and loss refines the AI prompts — output quality improves with use, not with more effort
- Every project delivered generates new case studies — harvest loop closes itself as Connected builds
- Every US engagement adds to a market intelligence base competitors cannot replicate
Department workflows
How each department interacts with the platform — their specific process flow, the tools they use, and the actions required from them. These sit beneath the master end-to-end workflow and can be extracted as standalone operational guides for each team.