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Kaya AI

AI-native procurement, equipment tracking, and delivery platform for mission-critical construction supply chains

Kaya AI is a cloud platform for data center and mission-critical construction projects that unifies RFP drafting, side-by-side bid leveling, owner-furnished/contractor-installed (OFCI) equipment tracking, and last-mile delivery scheduling. An AI agent branded "Amber" (referred to as "Jarvis" in early-2025 coverage) answers natural-language questions grounded in live project data and flags schedule risk across fabrication, shipping, and submittal-approval dependencies.

$5.3M pre-seed (announced January 2025), led by 53 Stations and Suffolk Technologies with participation from Soma Capital, Barclays Black Formation Investments (managed by Zeal Capital Partners), RXR, Mantis VC, Virta Ventures, 4DX Ventures, TO Ventures, Optimist Ventures, Refashiond Ventures, Timon Capital, BFF, and BlueImpact raisedEarly Stage
Founded 2023 · Customer count not publicly disclosed. Named case study: general contractor Suffolk (Suffolk Construction, an industry partner of investor Suffolk Technologies) adopted Kaya AI after its BOOST 4 accelerator cohort and reports reducing a three-month procurement process to one week on one project (self-reported by Kaya AI via press release, not independently audited). Kaya AI's own "Amber" product page also names Turner Construction as a user; this claim is unverified outside Kaya AI's marketing materials. Publicly launched from stealth in January 2025 after being founded in 2023.
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Why This Tool Exists

The Problem

On data center and mission-critical projects, procurement, owner-furnished equipment tracking, and jobsite delivery coordination typically live in disconnected tools, spreadsheets, calls, and email. Project managers often miss the dependencies between fabrication, shipping, and submittal approval, so schedule risk surfaces late; Kaya AI cites one general-contractor case where reconciling this manually took three months.

The Solution

Kaya centralizes RFP drafting/routing, AI-assisted bid leveling (cost, scope, schedule, and risk, with source-cited recommendations), OFCI equipment tracking from order to installation, and last-mile delivery scheduling in one system tied to live project documents. The "Amber" AI agent answers natural-language questions grounded in project data, proactively flags coordination risk, and automatically updates project timelines as submittals, bids, and deliveries change.

How You Use It

Delivery Method
SaaSWeb AppMobile App
Integrations
ProcoreAutodesk Construction Cloud (ACC)TrimbleSAPPeopleSoftOracle Primavera P6 and Bluebeam (per a Kaya AI "Construction AI Delivery Lead" job posting; not confirmed on official product/marketing pages)
Disciplines
Project Phases
Preconstruction, Bidding/Procurement, Construction Administration
Project Types
Data Centers, Industrial, Commercial

Data Transparency

Exactly what this tool uses and how

Input
What it needs
Required:Project drawings and specifications, Equipment/procurement lists, RFP and bid documents
Optional:Project schedule, Vendor/supplier contact and delivery data, Submittal logs
Formats:PDF, CAD/BIM (via Procore/Autodesk ACC integration), Excel/CSV, Email
Output
What you get
Format:Web dashboard, live delivery calendar, and conversational AI interface (Amber)
Fields:RFP drafts and tracked-change revisions, Bid comparison/leveling matrix (cost, scope, schedule, risk), OFCI equipment tracking status with risk flags, Delivery schedule and conflict alerts, Automatically updated project timelines, Natural-language answers to project questions, grounded in project data
Algorithm
How it works
Model:Multi-model architecture: third-party foundation models (OpenAI, Anthropic, Grok, and Cohere, per Kaya AI's own OFCI product page) plus a proprietary construction-specific embeddings/integration layer; exact model versions and fine-tuning approach not disclosed
Accuracy:Vendor claims an 80% reduction in procurement management time and a 90% improvement in lead-time accuracy, drawn from a single named case study (general contractor Suffolk) publicized in Kaya AI's own funding-announcement press release; not independently audited
Privacy
How your data is protected
Retention:Not publicly specified
Training:Not publicly specified
Compliance:SOC 2 (type not specified) claimed as of October 2, 2025 per Kaya AI's own blog post, audited by Advantage Partners with Vanta used for compliance automation; no public SOC 2 report or audit letter found
API
Integration
Endpoint:Not publicly documented; no self-serve API portal or developer docs found
Method:Not publicly specified

Use Cases

  • ·Drafting, routing, and revising RFPs for owner-furnished/contractor-installed (OFCI) equipment
  • ·Side-by-side AI bid leveling on cost, scope, schedule, and risk for mission-critical/data-center procurement
  • ·Tracking OFCI equipment from order through fabrication, shipping, and installation with automated risk flags
  • ·Coordinating last-mile jobsite deliveries via a live calendar with automated conflict resolution
  • ·Surfacing schedule risk from fabrication/shipping/submittal-approval dependencies before it causes delays

Pricing

Free
No public free tier; access is via "Book a Demo" enterprise sales process
Pro
Not publicly specified; contact vendor
Enterprise
Custom pricing based on project/portfolio scope; contact vendor
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Research Sources & Data QualityLast verified: 2026-07-17
Verified Data (10)
problem, solution, deliveryMethod, integrations (Procore, Autodesk ACC, Trimble, SAP, PeopleSoft per official OFCI product page), fundingTotal, yearFounded, founders (Ojonimi Bako, Nicholas Selz), customerBase (Suffolk case study, per vendor press release), SOC 2 compliance claim (per company blog), AI foundation-model stack (OpenAI/Anthropic/Grok/Cohere, per official product page)
Not Found (8)
pricing/fee structure, API documentation or endpoint, data retention policy, data training policy, data storage location/region, exact employee count (conflicting third-party directory data), independent verification of Turner Construction as a customer, independent audit of the claimed 80%/90% efficiency metrics
Our Commitment: We only include verified data from official sources. If information isn't publicly available, we mark it as "Not publicly specified" rather than guessing.