PWS LCAT Evaluator Agent

Corey Solivan

• Nov 2, 2025
• 4 min read

Updated: Nov 3, 2025

Data Room AI Launches the PWS LCAT Evaluator Agent — “No-Miss Coverage. Evidence-Based Sizing. FTEs You Can Defend.”

Naples, FL – October 31, 2025— Data Room AI (DRAI) today announced the launch of the PWS LCAT Evaluator Agent — a first-of-its-kind AI system that eliminates guesswork in proposal labor mapping, accelerating work breakdown structure (WBS) creation, ensuring no missed requirements, formulating evidence-based labor category selection, and defensible FTE sizing.

Built for proposal, pricing, and program management teams, the PWS LCAT Evaluator automatically parses Performance Work Statements (PWS) and Statements of Work (SOW), maps every clause to relevant labor categories (LCATs) and BLS Standard Occupational Classification (SOC) codes, and calculates precise FTE allocations tied to measurable Key Performance Indicators (KPIs).

“This isn’t just AI that reads — it reasons,” said Corey Solivan, Founder & CEO of Data Room AI. “The PWS LCAT Evaluator shows exactly how many people you need, the work breakdown structure for why you need them, and how to justify every hour internally or to the Government.”

🧩 Mission

To ensure that no PWS clause is missed, no labor role is unjustified, and no cost assumption goes unexplained.

The PWS LCAT Evaluator bridges the gap between technical scope and pricing reality, creating transparent, defensible, and data-backed labor plans — from opportunity pursuit through post-award execution.

⚙️ How It Works

1️⃣ User-Driven Initialization

Upload your PWS or SOW document and identify:

• Customer or agency (e.g., AFMC, DHS, GSA)
• Known incumbents or subcontractors

2️⃣ Customer & Incumbent Hiring Research

The agent conducts targeted web-scraping of official career portals for both the customer and known incumbents, building a Hiring Evidence Summary that includes:

• Role titles, clearance levels, and certifications
• Hiring locations, shifts, and pay bands
• Staffing patterns by role type (e.g., Cyber Analyst vs. Systems Engineer)

3️⃣ No-Miss PWS Parser (L1/L2 Control System)

The agent parses every clause, ensuring zero omissions across all “The Contractor shall…” statements.

It produces a Coverage Tracker showing full clause traceability:

L1

L2

Title

#Tasks

#Mapped

Unmapped?

1

1.1

Program Management

8

8

✅ OK

2

2.1

Network Operations

12

11

⚠️ [GAP: 1 unmapped task]

3

3.1

Cybersecurity Operations

10

10

✅ OK

5

5.3

Wireless/BITI Fielding

5

4

⚠️ Missing RF Test Engineer mapping

If any unmapped tasks are found, it pauses and flags for user confirmation: “L2-5.3 Wireless/BITI Fielding contains an unmapped task: ‘The Contractor shall perform on-site RF signal testing at CONUS/OCONUS locations.’ — Please assign an LCAT or [WAIVE] this gap.”

This guarantees full compliance coverage from PWS → LCAT → SOC.

4️⃣ Task → LCAT → SOC Mapping

Each clause is mapped to relevant labor categories and validated through evidence.

PWS Ref

Task Excerpt

Recommended LCAT

Job Evidence

SOC Code

2.1.3

Maintain and configure routing equipment.

Network Engineer

AFMC job post: “Network Engineer (TS/SCI, Cisco)”

15-1244

3.1.5

Conduct continuous vulnerability assessments.

Cybersecurity Analyst

Incumbent posting: “ISSO II, RMF, CCRI prep”

15-1212

5.3.2

Perform RF coverage tests.

RF Field Engineer

AFLCMC listing: “Wireless Spectrum Engineer (BITI)”

17-3023

This table forms the auditable backbone of cost realism and price-to-win modeling.

5️⃣ SOLVE: Obligations → Value → FTEs by LCAT

Once mappings are confirmed, the agent computes total staffing requirements using transparent math:

Example User Inputs:

• Total Obligations: $105M
• Period of Performance: 1 base + 4 option years
• Average Salary: $78,500
• Wrap Rate: 1.625

Outputs:

• Annualized Value = $21M/year
• Fully Burdened Cost/FTE = $127,562.50
• Total FTEs = 165 FTEs/year

LCAT

% Allocation

FTEs

Rationale

KPIs

Cybersecurity Analyst

18%

30

12 tasks (STIGs, RMF, CCRI)

95% STIG closure

Network Engineer

25%

41

9 uptime/patching tasks

99.95% uptime

RF Field Engineer

6%

10

BITI & RF testing tasks

100% coverage uptime

Program Manager

4%

7

Deliverable oversight

CPI ≥ 0.95

Service Desk Lead

10%

17

Ticket handling & escalation

CSAT ≥ 90%

Remaining Roles

37%

60

Other technical & OEM

SLA-based

Every assumption, variable, and KPI is exportable — ideal for DCAA audits or internal review.

6️⃣ KPI + Metric Integration

For every LCAT, the agent defines quantifiable, mission-linked performance metrics such as:

• Cyber: Mean Time to Detect (MTTD), CCRI readiness
• Network: Patch SLA %, uptime reliability
• Program Management: CPI/SPI, milestone completion rate
• RF/Wireless: Spectrum compliance, coverage uptime

7️⃣ Exports

Final deliverables are generated in XLSX, CSV, and Markdown formats for seamless integration into pricing models, proposal appendices, or audit binders.

🧮 Key Deliverables

Deliverable

Description

Audience

Coverage Tracker

Clause traceability with GAP logic

Proposal Managers

PWS → LCAT → SOC Table

Evidence-backed labor mapping

Pricing Analysts

FTE Solver Output

Transparent FTE computation

Finance / Executives

KPI Sheet

Quantifiable performance linkage

Program Teams

Hiring Evidence Summary

Real-world role validation

Capture Leads

🧭 Ideal Users

Role

Benefit

Pricing Analysts

FTE logic that stands up to DCAA and audit scrutiny

Proposal Managers

No-miss mapping and compliance visibility

Capture Managers

Incumbent and competitor staffing intelligence

Program Managers

KPI-linked staffing baselines for post-award tracking

🧩