PWS LCAT Evaluator Agent
Ensures total PWS/SOW coverage, maps scope tasks to the most relevant labor categories, performs salary survey research, builds cost-price analyst worksheets, and solves basis of estimate (BOEs) for price to win.
- Category
- GovCon Growth.
- Registry category
- Intelligence & ResearchResearch & Knowledge Intelligence
- Vendor
- Data Room AI (DRAI) (DRAI COMMERCIAL SERVICES INC)
- Location
- Naples, Florida 34120, United States of America
- Reviews
- This marketplace has no ratings
- Listed on
- DRAI Agentic-AI Marketplace
- Pricing
- Not stated
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What the publisher says
Data Room AI Launches the "PWS LCAT Evaluator" Agent
*
Corey Solivan
Show the rest of the publisher’s description (164 more lines)
- 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
🧩
Linked repositories
Unknown
Unknown means this listing does not publish a repository. It is not a statement that the code is closed.
Publisher resources
Sources
- Marketplace listingDRAI Agentic-AI Marketplace (opens in a new tab)
- Certification pagedrai-commercial.com (opens in a new tab)
- AI ethics statementdrai-commercial.com (opens in a new tab)Fetched and hashed
- Privacy policydrai-commercial.com (opens in a new tab)Fetched and hashed
- Security and compliance statementdrai-commercial.com (opens in a new tab)Fetched and hashed
- Terms of servicedrai-commercial.com (opens in a new tab)Fetched and hashed
- Company recordOutside company data, matched on drai-commercial.com
- Official registersam.gov (opens in a new tab)
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The SettleTop steps above are possible but not automated yet, so today they sit open and a perfect 10 is out of reach. Open information like firmographics and reach has fewer steps to climb, so it sits a little higher for the same visible evidence.
Information shown here reflects the best available information at the time of assessment and may be incomplete, outdated, or subject to change. It should be independently verified before being relied upon for any decision. SettleTop is not liable for any errors, omissions, or decisions made in reliance on this information.
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