Agentic systems are AI-powered tools that can take initiative—planning actions, making decisions, and adapting to changing inputs—rather than just reacting to static commands. Unlike traditional automation, which waits for instructions, agentic systems operate more like digital coworkers, proactively identifying what needs to happen next. In the AEC industry, this might look like an AI that monitors deadlines, flags missing content, recommends win themes, or auto-assigns tasks based on RFP requirements. Joist AI is moving toward this agentic model—helping teams go beyond automation to intelligent, collaborative pursuit management.
Architects lead the design and planning of buildings and spaces, balancing aesthetics, function, sustainability, and code compliance. They collaborate with clients, engineers, and consultants to bring a project’s vision to life—from conceptual design through construction documents. In proposal settings, Architects contribute design narratives, innovation highlights, and relevant project experience. Joist AI supports Architects by organizing language from past work, generating polished drafts, and reducing the time required to contribute valuable input—without disrupting their design responsibilities.
Artificial intelligence is a broad field focused on building systems that can mimic human cognitive abilities, such as learning, reasoning, and problem-solving. In practice, AI often involves machine learning, natural language processing, and other techniques that allow software to make decisions or generate content. For AEC firms, AI can accelerate proposal creation, automate content retrieval, and analyze project documents with remarkable speed. Joist AI uses these capabilities to help AEC teams respond to RFPs more effectively—by learning from past work, analyzing new documents, and generating responses with precision. Rather than replacing people, it enhances human expertise at scale. AI turns institutional knowledge into a competitive advantage.
An award submission is a curated document or package created to showcase a firm’s excellence on a particular project or initiative, typically in response to a call for entries by industry organizations. These submissions highlight innovation, design quality, community impact, or project delivery success. They often repurpose proposal materials but require a more narrative, visual, and compelling tone. Joist AI accelerates the award submission process by pulling from past project write-ups, tagging notable achievements, and generating polished content that aligns with award criteria.
A bid is a formal offer to deliver a project or service at a specified price, timeline, and scope—typically submitted in response to an RFP. In AEC, bids often involve both technical and cost proposals, and require precise coordination across estimators, engineers, and marketers. Winning a bid hinges on alignment between the client’s needs and the firm’s capabilities. Joist AI supports this process by enabling faster, more accurate technical proposal creation—so teams can focus on pricing and strategy.
Black-box AI refers to systems that make decisions or generate outputs without offering transparency into how those results were reached. This can make it difficult to validate accuracy, trace logic, or troubleshoot errors—especially in high-stakes environments like AEC proposals. Joist AI is designed to avoid this issue by grounding outputs in retrievable, source-linked content. That means users can see where the information came from, review sources, and maintain confidence in the final product.
Black-box AI refers to systems that make decisions or generate outputs without offering transparency into how those results were reached. This can make it difficult to validate accuracy, trace logic, or troubleshoot errors—especially in high-stakes environments like AEC proposals. Joist AI is designed to avoid this issue by grounding outputs in retrievable, source-linked content. That means users can see where the information came from, review sources, and maintain confidence in the final product.
Brand identity is the visual and verbal expression of your firm’s brand—how it looks, feels, and communicates across all channels. It includes your logo, color palette, typography, tone, and messaging. In AEC marketing, a strong brand identity helps firms stand out in a crowded field and builds familiarity with clients. Joist AI helps uphold brand identity by leveraging your brand and messaging guidelines, keeping your team consistent and on brand, even across multiple geographical regions.
Brand voice is the distinct personality and tone that a firm uses in its written and spoken communications. For AEC firms, it reflects how you want clients to perceive you—whether that’s as technical experts, trusted partners, or creative problem-solvers. Maintaining a consistent brand voice across pursuits builds trust and reinforces differentiation. Joist AI helps preserve and replicate brand voice by learning from your past proposals and applying your style preferences to every draft.
Business development in the AEC industry refers to all the activities that generate new opportunities and relationships—before a formal RFP ever hits your inbox. It includes networking, client outreach, market research, and positioning your firm for future work. BD professionals lay the groundwork that marketing and technical teams build on during a pursuit. Joist AI supports business development by helping teams track pursuits, identify relevant past work, and quickly tailor content to nurture leads and win trust.
BD Directors and Managers identify new opportunities, build client relationships, and drive pursuit strategy. They often coordinate with technical teams and marketing to ensure client needs are met and expectations are exceeded. When repeat business or contract expansions arise, they play a key role in shaping pursuit strategy and facilitating responses. Joist AI supports BD leaders by surfacing relevant experience, helping tailor messaging for target clients, and generating early-stage materials that help warm leads before the RFP drops.
Chain of thought is a reasoning technique used by AI models to solve problems step by step—just like a person might talk through their thinking before arriving at a conclusion. Instead of jumping straight to an answer, the AI explains its logic, which helps improve accuracy and transparency. In the context of AEC marketing, this is especially useful for complex prompts like scoring an RFP, drafting a project approach, or justifying a win theme. Joist AI applies chain of thought reasoning to help users trace how responses are generated—making it easier to review, edit, and trust the final output.
A prompt chain breaks a complex task into smaller, sequenced steps. Each output feeds into the next prompt. This helps AI stay focused and reduces errors. It’s like giving directions one turn at a time instead of handing someone a full map. Joist AI uses this approach internally in certain workflows, such as using the RFP to generate proposal outlines section by section, ensuring focus and coherence. It's ideal for longform content like cover letters or detailed methodology sections. The result is smarter structure and less editing.
Example: Instead of asking the AI to “write a complete project approach,” a prompt chain might start with “summarize the client’s priorities,” then use that output to prompt “list the key project phases,” followed by “describe how our team will manage each phase,” and so on—building the section logically and collaboratively.
A chatbot is a software application designed to simulate conversation with users—often through text, and sometimes via voice. Chatbots can answer questions, direct users to information, or handle simple tasks. Unlike traditional chatbots, Joist AI is powered by a large language model, enabling it to understand context and generate thoughtful, domain-specific responses. But Joist goes further—it incorporates structured workflows, retrieval systems, and content templates to deliver accurate, workflow-specific results. Rather than just answering questions, Joist functions as a strategic assistant purpose-built for AEC proposal teams—guiding users through complex tasks, not just chatting at them.
The Chief Growth Officer is responsible for driving firm-wide growth by aligning business development, marketing, and strategic initiatives. In AEC firms, this often means expanding into new markets, optimizing pursuit processes, and improving win rates. CGOs rely on tools that help their teams respond faster, maintain consistency, and increase output without increasing headcount. Joist AI supports this mandate by accelerating proposal creation, streamlining access to firm knowledge, and enabling teams to pursue more opportunities with greater confidence.
The Chief Innovation Officer is tasked with identifying, evaluating, and implementing emerging technologies that can create competitive advantage and operational efficiency. In AEC firms, this includes exploring AI, automation, and digital collaboration tools that enhance how teams work and win. CINOs are often looking for tangible, scalable improvements—not just new tech for tech’s sake. Joist AI supports this mission by modernizing proposal development workflows, reducing reliance on manual effort, and demonstrating how AI can create immediate, measurable impact across pursuit and marketing operations.
The Chief Marketing Officer leads firm-wide brand strategy, marketing operations, and pursuit enablement—ensuring the firm presents a unified, compelling voice in every client interaction. In AEC firms, this role often spans everything from thought leadership to proposal systems to business development alignment. CMOs care about speed, quality, and consistency across distributed teams and regions. Joist AI supports CMOs by helping teams produce branded, compliant content at scale—reducing bottlenecks, shortening timelines, and unlocking more capacity for strategic initiatives.
The Chief Strategy Officer drives long-term growth by shaping market positioning, guiding firm priorities, and overseeing competitive and client intelligence. In AEC firms, CSOs often bridge business development, marketing, and operations to ensure strategic alignment. While they may not manage proposals directly, they care deeply about how the firm presents itself in pursuit efforts. Joist AI supports this role by standardizing messaging, improving responsiveness, and making it easier for teams to articulate value across sectors and client types.
Civil Engineers design, plan, and oversee the construction of infrastructure projects such as roads, bridges, water systems, and site developments. Their work involves technical analysis, permitting, and coordination across disciplines to ensure safety, compliance, and performance. In the context of proposals, Civil Engineers contribute scope details, methodologies, and QA/QC protocols that showcase the firm’s technical credibility. Joist AI reduces the burden on Civil Engineers by generating draft narratives, formatting resumes, and surfacing relevant project descriptions—so they can contribute efficiently without pulling away from billable work.
Client Services Directors manage key relationships and ensure long-term client satisfaction. They play a role in cross-selling and strategic positioning. Joist AI enables them to understand pursuit requirements, align content to client needs, and deliver consistent messaging across touchpoints.
Close-out in AEC marketing refers to the process of wrapping up a pursuit after submission. This may include debriefs with internal teams, saving and tagging final documents, recording outcomes, and documenting lessons learned. It’s a key opportunity to improve future pursuits and track win/loss trends. Joist AI helps teams close out effectively by organizing proposal artifacts, tagging key content for reuse, and generating summaries that capture what worked—and what didn’t.
This role sets the tone and voice of the firm—often overseeing both internal messaging and outward-facing communications like proposals, award submissions, and thought leadership. Joist AI supports them by enforcing brand voice, applying templates, and helping teams generate on-brand content at scale—without compromising quality.
Compliance in AEC marketing refers to how closely a proposal or qualifications submittal follows the specific requirements outlined in an RFP or RFQ. This includes formatting rules, page limits, section order, forms, and submission methods. Non-compliance can result in automatic disqualification—even if your content is strong. Joist AI supports compliance by checking for required elements, mirroring structure, and flagging missing sections early in the process, helping teams submit with confidence.
In CMAR, the construction manager commits to a guaranteed maximum price early in the project. They act as both advisor and builder. It’s a popular method for balancing cost control with schedule flexibility. Owners benefit from early cost insights and collaborative planning.
A content library is a centralized repository where firms store reusable marketing and proposal materials—such as resumes, project descriptions, boilerplate language, graphics, and templates. In AEC marketing, an organized content library saves teams time, ensures consistency, and reduces duplication. The challenge is keeping it updated and searchable. Joist AI turns your content library into a dynamic, intelligent system—automatically tagging assets, surfacing relevant content, and learning what gets used most to continually improve access.
Contextual prompting involves supplying the AI with relevant background information—such as past projects, client preferences, or company standards—to help it generate more accurate, tailored content. The more useful context the AI has, the stronger and more customized the output. Joist AI uses contextual prompting behind the scenes by drawing from your firm’s historical proposals, resumes, and narratives to inform each response. This ensures that content aligns with how your team has communicated in the past, making outputs feel both familiar and client-specific without requiring users to restate the details.
In the AI context, a copilot is a digital assistant that works alongside a human to support complex tasks—rather than automate them entirely. It augments decision-making by offering suggestions, drafting content, surfacing relevant information, or executing repetitive actions. Joist AI functions as a copilot for AEC proposal teams, helping marketers and technical staff work faster and smarter without replacing their expertise. The goal is not to take over the process, but to reduce the friction within it.
A cover letter is the first impression in any proposal submission. It introduces the team, affirms understanding of the client’s goals, and sets the tone for the rest of the document. A well-crafted cover letter is personalized and persuasive, rather than generic or overly formal. It often reflects the firm's voice and highlights its alignment with the project vision.
A CRM is your central hub for managing clients, prospects, and opportunities. From tracking outreach to storing contact details, it keeps sales and marketing aligned. In the AEC industry, it’s especially helpful for managing long sales cycles and complex stakeholder networks. Joist AI integrates with some CRM systems to pull in relationship data and ensure generated proposal content aligns with account context, helping teams maintain a single source of truth across marketing and business development.
A traditional project delivery method where design and construction are separate contracts. It’s linear, familiar, and widely used—but can be slower or riskier if coordination breaks down. Design is completed before construction begins, which gives the owner greater control but limits early collaboration.
A project delivery method that combines design and construction under one contract, fostering collaboration and speed. It’s gaining traction for its efficiency, especially when time-to-completion is critical. This approach allows for overlapping phases and streamlined communication.
Digital assets are the files and media your firm uses to communicate and market—think logos, photos, diagrams, infographics, boilerplate language, and video reels. In AEC marketing, these assets are critical for maintaining brand consistency across proposals and collateral. Organizing and retrieving them efficiently can make or break a tight submission timeline. Joist AI enhances digital asset usage by tagging, indexing, and surfacing the right files at the right time—so your best content never gets buried.
Digital Asset Managers (or DAM systems for short) store and organize your content—images, templates, diagrams, boilerplate language, and more. They’re essential when you're managing dozens of proposals and marketing assets. A strong DAM makes finding the right file as easy as typing a few keywords. It ensures brand consistency and reduces redundant work.
The Director of Operations oversees staffing, resource allocation, and project delivery workflows across the firm. In AEC organizations, they ensure that teams are properly assigned, deadlines are met, and project commitments align with available capacity. While not always directly involved in proposals, their role is crucial to maintaining balance between pursuit activity and billable work. Joist AI supports operational leaders by making staff experience easily searchable, simplifying resume generation, and enabling more informed decisions about team deployment during active pursuits.
A due diligence questionnaire is a detailed request for operational, legal, financial, or compliance-related information—typically issued before a partnership or contract is finalized. In the AEC space, DDQs often surface during private-sector pursuits, vendor onboarding, or mergers and acquisitions. They can be time-consuming to complete, requiring coordination across legal, finance, HR, and marketing teams. Joist AI streamlines the DDQ process by organizing previously submitted answers and ensuring consistent, compliant responses across the firm.
Embedding is the process of turning text into numerical vectors so that it can be compared or searched semantically. Joist AI uses embeddings to match prompts with the most relevant content in your library—even when the words don’t exactly match. It’s how the system “understands” that “stormwater management” and “drainage design” might mean the same thing in a given context.
ERP systems help firms manage their day-to-day operations in one place. This includes things like staffing, budgets, schedules, and invoices. While CRMs focus on external relationships, ERPs focus on internal resources—making sure the right people, time, and money are in place to deliver projects. In AEC firms, ERPs are critical for keeping projects on track and managing workloads across teams.
Explainability refers to how clearly an AI system can show the reasoning behind its outputs. It builds trust and allows users to validate content before using it. Joist AI supports explainability by referencing source materials, showing search queries generated as part of a chat, and making it easy to trace where content came from.
A fee proposal—or fee letter—is a document that outlines the costs associated with delivering a project, often submitted alongside or after a technical proposal. It typically includes breakdowns by phase, discipline, or task, and sometimes references contract terms. In AEC, these documents must be clear, accurate, and defensible—especially in competitive or public-sector bids. Joist AI helps by generating consistent narrative components, allowing fee writers to focus on pricing details without rewriting project descriptions or scope overviews.
Few-shot prompting gives the AI multiple examples to mimic. This helps improve output quality, especially for nuanced or high-stakes tasks. It’s like showing, not just telling. In technical or regulatory responses, this method produces more relevant and confident content.
A foundational model is a large, pre-trained AI model that powers more specific applications. It’s trained on massive datasets and can be fine-tuned for industry use. These models are the base layer of tools like Joist AI and serve as general-purpose engines that can be directed with prompts. Joist AI builds on these models with AEC-specific training and retrieval techniques. That’s how it understands the difference between “project approach” and “scope creep.”
The go/no-go process is a structured decision-making step where AEC firms evaluate whether to pursue a specific opportunity. It considers factors like client fit, scope, competition, resources, and win probability. Making smart go/no-go decisions improves hit rates and protects teams from burning out on low-probability pursuits. Joist AI supports this process by helping firms assess pursuit history, analyze opportunity alignment, and surface relevant data to inform strategic calls.
A go/no-go scorecard is a structured tool used to evaluate whether an AEC firm should pursue a project opportunity. It includes weighted criteria such as client relationship strength, project fit, team availability, and potential for repeat work. By scoring each factor, teams can make more objective, consistent decisions. Joist AI can support this by surfacing similar project data, organizing relevant pursuit history, and helping teams make informed, timely decisions during early bid evaluation
These visual communicators turn ideas into polished, on-brand layouts and graphics. Joist AI helps by keeping content structured and editable, reducing back-and-forth over text changes and allowing designers to focus on high-impact visuals.
In the context of AI, hallucination refers to when a language model generates content that sounds plausible but is factually incorrect or entirely made up. This can include invented project names, inaccurate firm credentials, or fabricated client quotes. In high-stakes documents like AEC proposals, hallucinations can damage credibility and lead to disqualification. Joist AI reduces hallucination by using retrieval-augmented generation (RAG) to ground responses in your firm’s actual project history, resumes, and past proposals.
Hit rate is the ratio of proposals won to those submitted, often expressed as a percentage. It's a critical metric for marketing and business development teams to track the effectiveness of their pursuit efforts. A rising hit rate may reflect stronger qualification, messaging, or targeting strategies. Conversely, a low hit rate may signal the need to reassess go/no-go decisions or improve proposal quality.
HITL means keeping humans involved in the AI process, especially for tasks that require judgment, creativity, or compliance. Joist AI is designed to augment—not replace—marketers, SMEs, and proposal managers. It gets you to a quality first draft so your team can focus on the polish.
These are your trusted building blocks—ready-made content you reuse often. From company overviews to project win themes, this content saves time and ensures consistency. When properly managed, these narratives help maintain brand voice and reduce the effort needed to respond to common RFP questions.
