* { box-sizing: border-box; }

body {

margin: 0;

padding: 0;

font-family: system-ui, -apple-system, BlinkMacSystemFont, "SF Pro Text",

"Segoe UI", sans-serif;

background: radial-gradient(circle at top left, #1a2850 0, #050816 45%, #02010b 100%);

color: var(--text-main);

}

a { color: var(--accent-soft); text-decoration: none; }

.page {

max-width: 1120px;

margin: 32px auto;

padding: 24px 20px 40px;

}

.shell {

border-radius: 24px;

background:

radial-gradient(circle at top left, rgba(255,255,255,0.08) 0, transparent 55%),

radial-gradient(circle at bottom right, rgba(77,208,225,0.18) 0, transparent 60%),

linear-gradient(135deg, rgba(255,255,255,0.08), rgba(10,15,35,0.98));

padding: 1px;

box-shadow:

0 24px 80px rgba(0,0,0,0.8),

0 0 0 1px rgba(148,163,255,0.12);

}

.inner {

border-radius: 23px;

background: radial-gradient(circle at top, #0a0f23 0, #050816 55%, #02010b 100%);

padding: 28px 28px 32px;

}

.eyebrow {

display: inline-flex;

align-items: center;

gap: 8px;

padding: 4px 10px;

border-radius: 999px;

background: rgba(15,23,42,0.85);

border: 1px solid rgba(148,163,255,0.4);

font-size: 11px;

letter-spacing: 0.12em;

text-transform: uppercase;

color: var(--accent-soft);

margin-bottom: 16px;

}

.eyebrow-dot {

width: 7px;

height: 7px;

border-radius: 999px;

background: radial-gradient(circle at 30% 30%, #fff 0, #ffb347 35%, #ff6b6b 75%);

box-shadow: 0 0 12px rgba(255,107,107,0.65);

}

.hero {

display: grid;

grid-template-columns: minmax(0, 3fr) minmax(0, 2.3fr);

gap: 32px;

align-items: flex-start;

}

h1 {

margin: 0 0 12px;

font-size: clamp(28px, 3vw, 34px);

letter-spacing: 0.03em;

}

.hero-title-gradient {

background: linear-gradient(110deg, #ffffff, #ffd4a3, #4dd0e1);

-webkit-background-clip: text;

background-clip: text;

color: transparent;

}

.hero-sub {

font-size: 14px;

color: var(--text-muted);

max-width: 520px;

line-height: 1.5;

}

.pill-row {

display: flex;

flex-wrap: wrap;

gap: 6px;

margin-top: 12px;

}

.pill {

font-size: 11px;

padding: 3px 9px;

border-radius: 999px;

border: 1px solid rgba(148,163,255,0.35);

background: rgba(15,23,42,0.9);

color: var(--accent-soft);

white-space: nowrap;

}

.metric-card {

border-radius: 18px;

padding: 16px 16px 14px;

background: radial-gradient(circle at top left, rgba(255,255,255,0.08) 0, transparent 55%),

linear-gradient(145deg, #050816, #0d1228);

border: 1px solid rgba(148,163,255,0.3);

box-shadow: 0 18px 50px rgba(0,0,0,0.7);

}

.metric-grid {

display: grid;

grid-template-columns: repeat(3, minmax(0, 1fr));

gap: 10px;

margin-top: 10px;

}

.metric-label {

font-size: 10px;

text-transform: uppercase;

letter-spacing: 0.14em;

color: var(--text-muted);

margin-bottom: 4px;

}

.metric-value {

font-size: 18px;

font-weight: 600;

}

.metric-caption {

font-size: 11px;

color: var(--text-muted);

margin-top: 2px;

}

.tagline {

font-size: 11px;

color: var(--text-muted);

margin-top: 10px;

}

.divider {

margin: 22px 0 18px;

border: 0;

border-top: 1px solid rgba(148,163,255,0.25);

}

.section-grid {

display: grid;

grid-template-columns: minmax(0, 2fr) minmax(0, 2.2fr) minmax(0, 2.1fr);

gap: 18px;

}

.section-title {

font-size: 13px;

text-transform: uppercase;

letter-spacing: 0.18em;

color: var(--text-muted);

margin-bottom: 8px;

}

.card {

border-radius: 16px;

padding: 12px 13px 11px;

background: var(--card-bg);

border: 1px solid var(--border-soft);

}

.card h3 {

margin: 0 0 6px;

font-size: 14px;

}

.card p {

margin: 0 0 4px;

font-size: 12px;

color: var(--text-muted);

}

.card ul {

padding-left: 16px;

margin: 6px 0 0;

}

.card li {

font-size: 12px;

color: var(--text-muted);

margin-bottom: 2px;

}

.accent {

color: var(--accent-soft);

}

.usecases {

display: grid;

grid-template-columns: repeat(4, minmax(0, 1fr));

gap: 12px;

margin-top: 6px;

}

.usecase-card {

border-radius: 14px;

padding: 10px 10px 9px;

background: radial-gradient(circle at top, rgba(255,255,255,0.07) 0, rgba(5,8,22,0.98) 52%);

border: 1px solid rgba(148,163,255,0.4);

}

.usecase-label {

font-size: 10px;

text-transform: uppercase;

letter-spacing: 0.16em;

color: var(--accent-2);

margin-bottom: 3px;

}

.usecase-title {

font-size: 12px;

font-weight: 600;

margin-bottom: 4px;

}

.usecase-card ul {

margin: 4px 0 0;

padding-left: 14px;

}

.usecase-card li {

font-size: 11px;

color: var(--text-muted);

margin-bottom: 2px;

}

.ref-grid {

display: grid;

grid-template-columns: minmax(0, 2.2fr) minmax(0, 2.2fr) minmax(0, 2fr);

gap: 12px;

margin-top: 8px;

}

.ref-card {

border-radius: 14px;

padding: 10px 11px 9px;

background: #050816;

border: 1px solid rgba(148,163,255,0.35);

}

.ref-tag {

font-size: 10px;

text-transform: uppercase;

letter-spacing: 0.16em;

color: var(--text-muted);

margin-bottom: 3px;

}

.ref-card h3 {

margin: 0 0 4px;

font-size: 13px;

}

.ref-card p {

margin: 0 0 4px;

font-size: 11px;

color: var(--text-muted);

}

.ref-card ul {

margin: 4px 0 0;

padding-left: 14px;

}

.ref-card li {

font-size: 11px;

color: var(--text-muted);

margin-bottom: 2px;

}

.footer-note {

margin-top: 16px;

font-size: 10px;

color: var(--text-muted);

opacity: 0.9;

}

@media (max-width: 960px) {

.hero {

grid-template-columns: minmax(0, 1fr);

}

.metric-grid {

grid-template-columns: repeat(3, minmax(0, 1fr));

}

.section-grid {

grid-template-columns: minmax(0, 1fr);

}

.usecases {

grid-template-columns: repeat(2, minmax(0, 1fr));

}

.ref-grid {

grid-template-columns: minmax(0, 1fr);

}

@media (max-width: 640px) {

.inner {

padding: 20px 16px 22px;

}

.metric-grid {

grid-template-columns: repeat(2, minmax(0, 1fr));

}

.usecases {

grid-template-columns: minmax(0, 1fr);

}

<div>

<h1>

Supercharge <span class="hero-title-gradient">utilization, M&A integration, and AI impact</span> at LJA.

</h1>

LJA is an employee-owned, multi-disciplinary firm with ~2,000 employees across eight sectors and 25+ acquisitions in the last two years — but knowledge lives in too many places, Copilot hasn’t delivered, and utilization is stuck near ~70%.

</p>

<span class="pill">Lift utilization 3–5 pts by shrinking “search tax” and rework</span>

<span class="pill">Turn M&A sprawl into an integrated knowledge advantage</span>

<span class="pill">Make AI useful beyond Office: engineers, IT, and pursuits</span>

</div>

<div class="section-title">North-star impact for LJA</div>

<div>

<div class="metric-label">Engineer time</div>

Per engineer by cutting time spent hunting for specs, drawings, and prior work — a 3–5% utilization lift in an employee-owned model.

</div>

<div>

<div class="metric-label">Proposals & RFQs</div>

<div class="metric-value accent">~50% faster</div>

Auto-assemble resumes, project stories, and boilerplate from wins to raise throughput & win-rate with Land Dev & Public Works owners.

</div>

<div>

<div class="metric-value accent">L1/L2 deflection</div>

Use Glean as the safe, enterprise AI layer for L1/L2 tickets, Copilot gaps, and AI experiments — governed centrally by IT & the AI Committee.

</div>

Glean becomes the AI “system of context” across LJA’s Microsoft estate, file servers, ProjectWise/Ignite, Freshservice, Salesforce, and more — so every engineer, PM, and pursuit team has the full story in one place.

</p>

</div>

<div class="section-title">LJA today</div>

<h3>High-performing, but constrained by knowledge friction</h3>

<p>

<span class="accent">Who LJA is.</span> Employee-owned consulting engineering firm across the Southeast & Texas; ~2,000 employees across eight core sectors (Public Works, Transportation, Land Development, Energy, Environmental, Surveying, Rail). Land Development is the biggest revenue driver and highly influential.

</p>

<p>

<span class="accent">How they grow.</span> 25+ acquisitions over the last two years with more planned — mostly smaller regional firms with their own tech stacks, SharePoint sites, file servers, and engineering systems.

</p>

<p>

<span class="accent">Where it hurts.</span>

</p>

<ul>

<li>Utilization hovering around ~70% — much of the “missing” 30% is non-billable search, onboarding, and rework time.</li>

<li>Knowledge fragmentation and “tribal knowledge” risk across autonomous BUs, regions, and acquired firms.</li>

<li>Proposal velocity strain and desire to get more bids out, faster, without sacrificing quality.</li>

<li>AI Committee has piloted Copilot for ~6 months with low adoption and unclear value; IT sees it as “very basic.”</li>

<li>L1/L2 ticket resolution is a 2026 priority for IT leadership, but knowledge is scattered across SharePoint, file shares, ProjectWise, Ignite, and Freshservice.</li>

</ul>

</article>

<div class="section-title">What Glean is</div>

<h3>The Work AI platform built for firms like LJA</h3>

<p>

<span class="accent">AI system of context.</span> Glean unifies content, people, projects, and decisions in an Enterprise Graph — across M365, file servers, engineering repos, ticketing, CRM, and more — with real-time, permissions-aware security.

</p>

<p>

<span class="accent">Search + Assistant + Agents.</span> One interface where engineers can search, ask natural language questions, and trigger task-specific agents (e.g., “Find similar stormwater projects,” “Draft RFI response,” “Summarize spec changes since last issue”).

</p>

<p>

<span class="accent">Open and horizontal.</span> 100+ connectors and actions, multi-LLM support, and an agent platform IT can govern — so LJA can bring its own tools, models, and partner ecosystem (e.g., Alchemy) into one AI fabric instead of betting everything on a single vendor’s walled garden.

</p>

<p>

<span class="accent">Enterprise-grade security.</span> Single-tenant architecture, real-time permission sync, and Glean Protect guardrails so AI only shows what a user is allowed to see — critical for regulated projects, client confidentiality, and cyber posture.

</p>

</article>

<div class="section-title">Business outcome targets</div>

<h3>Translate AI into utilization, velocity, and risk reduction</h3>

<ul>

<li><strong>+3–5 pts utilization</strong> by giving every engineer back 1–2 billable hours per week through instant access to prior designs, calcs, and decisions instead of re‑creating work.</li>

<li><strong>50% faster proposal cycles</strong> by auto-assembling resumes, relevant projects, and boilerplate from a unified knowledge base — matching what peer firms are already doing with Glean.</li>

<li><strong>IT & AI governance wins</strong> by consolidating “random acts of AI” into a governed platform, reducing shadow-GPT usage and oversharing risk while enabling high-value agents.</li>

<li><strong>Faster value from acquisitions</strong> by letting newly acquired teams search across legacy environments on day one, before tech stacks are fully rationalized.</li>

</ul>

</article>

</section>

<div class="section-title">High-impact use cases for LJA</div>

<div class="usecase-title">Engineer productivity & utilization</div>

<ul>

<li>Unified search across specs, CAD/PDFs, RFIs, submittals, and past projects — regardless of which BU or acquisition they came from.</li>

<li>“What did we do last time?” answers that pull in drawings, calcs, and narrative from similar projects with citations back to source docs.</li>

<li>Onboarding new engineers with self-service answers instead of constant interruptions to senior staff, lifting both parties’ utilization.</li>

</ul>

</article>

<div class="usecase-title">Proposals, RFQs & pursuits</div>

<ul>

<li>Auto-curate project write‑ups, resumes, and methods from prior wins by sector (e.g., Land Dev, Public Works, Transportation) into a first‑draft proposal package.</li>

<li>Reuse language and differentiators that worked for similar owners and project types instead of reinventing every time.</li>

<li>RFP / SOQ agents that cut assembly time from days to hours while improving consistency and win rate — already live at peer firms.</li>

</ul>

</article>

<div class="usecase-title">M&A knowledge integration</div>

<ul>

<li>Search across legacy SharePoint, on‑prem file servers, and tools like ProjectWise/Ignite as if they were one system — without forcing immediate migrations.</li>

<li>Quickly surface experts, precedents, and standards from acquired firms so their know‑how becomes an asset, not a liability.</li>

<li>Reduce risk that key knowledge “walks out the door” when local leaders or niche specialists leave.</li>

</ul>

</article>

<div class="usecase-title">IT, support & safe AI adoption</div>

<ul>

<li>L1/L2 support agent that suggests answers from Freshservice, runbooks, and prior tickets directly inside the help desk and Teams.</li>

<li>Governed alternative to ad‑hoc Copilot / GPT usage, with permissions, logging, and policy controls that meet LJA’s security bar.</li>

<li>Central AI hub IT can extend with new agents (e.g., spec/standard lookup, code compliance QA, “what changed between these drawings?”).</li>

</ul>

</article>

</div>

</section>

<div class="section-title">Lookalike stories LJA can point to</div>

<div class="ref-tag">General contractor / consulting engineering peer</div>

<h3>McCarthy: from stalled Copilot trial to firm‑wide AI foundation</h3>

<p>

McCarthy, a large GC with heavy healthcare / education / infrastructure work, went from an underwhelming Copilot experience to a Glean deployment that became one of the most adopted tools in the company.

</p>

<ul>

<li><strong>North star:</strong> shrink “bid to breaking ground” cycle time by ~75% by attacking knowledge & coordination bottlenecks.</li>

<li><strong>Adoption:</strong> grew from ~20 early users to wall‑to‑wall rollout (thousands of employees) within months, with >80% weekly active usage.</li>

<li><strong>Time savings:</strong> hours back per employee per week by reducing search and rework — across field, PM, and back‑office teams.</li>

<li><strong>Agents LJA will care about:</strong>

<ul>

<li>Management System agent to interpret 2,000+ procedures and standards in real time.</li>

<li>CMiC ERP onboarding agent (YouTube‑style walkthroughs) used tens of thousands of times.</li>

<li>Benefits Q&A agent reducing HR question volume.</li>

<li>RFP automation and “SubScout” agents that assemble 10+ years of project history, contracts, and performance data into bid content in under an hour.</li>

</ul>

</li>

</ul>

<p>

This is the closest “storyboard” for LJA’s world: multi‑office, project‑driven, engineering‑centric, and initially disappointed by Copilot before pivoting to Glean.

</p>

</article>

<div class="ref-tag">Power & infrastructure consulting engineering</div>

<h3>Firms like Sargent & Lundy & Thornton Tomasetti</h3>

<p>

In Glean’s AEC & engineering focus area, nuclear / power engineering leaders like Sargent & Lundy and structural specialists like Thornton Tomasetti show how Work AI can operate in highly regulated, safety‑critical environments.

</p>

<ul>

<li>Unifying drawings, specs, codes, and procedures across nuclear, grid, and conventional power portfolios while respecting strict permissioning and QA requirements.</li>

<li>Helping engineers answer “what did we do last time on a similar unit / structure?” with full traceability back to licensed calculations and approved designs.</li>

<li>Supporting digital modernization programs and early AI initiatives without forcing engineers to change their core design tools overnight.</li>

</ul>

<p>

These stories give LJA’s IT, safety, and sector leaders confidence that Work AI can be deployed responsibly in complex, regulated engineering contexts.

</p>

</article>

<div class="ref-tag">Diversified industrial & M&A heavy</div>

<h3>Koch: using Glean to turn acquisitions into compounding value</h3>

<p>

Koch Industries uses Glean as an “Expert AI Assistant” across 1.2B+ documents, 15k knowledge workers, and 50+ enterprise systems — an extreme case of the M&A and BU fragmentation LJA is starting to feel.

</p>

<ul>

<li><strong>Pre‑deal:</strong> identify internal experts to vet new investment opportunities (e.g., wind, cyber) by searching skills and work history across the entire enterprise.</li>

<li><strong>Post‑deal:</strong> avoid rushing tech migrations by letting teams search across legacy and new environments on day one, accelerating value realization.</li>

<li><strong>Day‑to‑day:</strong> help engineers and business teams bring new products to market ~20% faster by shrinking information‑retrieval and coordination time.</li>

</ul>

<p>

For LJA’s pipeline of 20–30 acquisitions per year, Koch is a proof point that AI‑driven knowledge integration can scale without forcing every acquired firm into the same tools overnight.

</p>

</article>

</div>

</section>

Note: Metrics and stories above are drawn from Glean customer materials and internal value hypotheses; tailor which proof points you use based on audience (e.g., executive, IT, or practice leaders) and confidentiality needs.

</p>

</div>

</section>