MAESTRO

MAESTRO

AI Orchestration Control Plane

Multi-agent enterprise supervisor that turns chaos into symphony. A fleet of specialized AI agents monitor infrastructure, triage incidents, review code, reconcile finance and revenue data, and handle recurring engineering and ops work around the clock — all dispatched from one control plane, with typed agent governance and per-engineer AI usage tracking built in from the ground up.

API Docs

Live — running production workloads today

Musicians

A fleet of specialized AI agents — each one a virtuoso in its domain.

🛒

Order Failure Analyst

Recurring analysis of failed orders across a monitoring platform. Classifies by failure type, emails reports, suggests fixes from a self-learning knowledge base.

🚨

SRE Monitor & Incident Response

24/7 monitoring of violations, app health, and infrastructure. Auto-pages on-call, threads updates in Slack, and kicks off a research/triage agent the moment an incident fires.

📈

Revenue Lifecycle Auditor

Contract → Order → Invoice → Cash → GL → Deferred Revenue → Recognition. Full chain-of-custody audit trail.

💵

Collections Tracker

AR aging analysis, DSO trends, tiered escalation letters. Automated follow-up cadence by severity.

🔒

Secret Scanner

Credential scanning across git history, cloud storage, containers, and chat. Verifies whether a found secret is still live before it's flagged.

🏃

Sprint Metrics

Sprint velocity, burndown, carry-over analysis. Global and team-level reports for engineering leadership.

👥

Capacity Planner

Headcount × PTO × on-call × velocity → real sprint capacity. Predicted velocity + recommended commitment.

📄

Contract Reconciler

Order-to-contract reconciliation — flags orphans, pricing variance, template mismatches across the contract hierarchy.

🏭

Intercompany Reconciler

Cross-entity matching, FX consistency checks, elimination entries for multi-entity accounting compliance.

💻

Automated Code Review

Reviews pull requests on demand, flags real issues before merge, and stays out of the way when there's nothing to say.

🧭

Self-Service Agent Creation

Describe the job in plain language and get a new purpose-built agent, live and dispatchable, with no engineering ticket required.

Platform

Enterprise-grade orchestration with SOC 2 / ITIL alignment.

🔐

RBAC + Multi-Tenant

Conductor / Section Lead / Player roles. Tenant domain enforcement, per-tenant config, MFA/SSO requirements.

📧

Automated Reports

Daily email digests via AWS SES. HTML reports with KPI cards, failure breakdowns, fix suggestions — delivered to your inbox.

📚

Knowledge Base

Self-learning pattern library. Each confirmed fix increases confidence. Auto-fixable entries queued for remediation.

☁

Cloud Intelligence

AWS cost analysis, resource classification, untagged spend detection. "Do It" buttons for one-click remediation.

🚀

Shipyard Integration

Specs → Shipyard pipelines → code changes. Branch isolation, stage validation, callback-driven lifecycle.

🎶

Harmony Voice

Natural language interface to the control plane. Ask questions, run analyses, dispatch specs — all by conversation.

📜

SIGHT — Living Requirements

Harbor's structured wiki layer: a hierarchical requirements/architecture tree with revision history and full-text search. Agents read SIGHT pages as live context when generating a spec, so runbooks and decisions stay in sync with what actually gets built — and an edit to a SIGHT page can itself trigger a review pass that opens follow-up work when the change implies code needs to catch up.

📋

Config Drift Watch

Periodic snapshots of a target service's configuration. Alerts on unexpected changes, dropped fields, or setting flips before they become a support ticket.

AI Governance & Tracking

Every agent typed, scoped, and audited — every dollar of AI spend attributed.

🏷

Typed Agent Scopes

Every agent declares itself read-only or action-taking, with exact write scopes at decoration time. Out-of-scope calls raise and page a human — no silent overreach.

📋

Hash-Chained Audit Trail

Every agent action logs a hash-chained record of what ran, what scope it declared, and whether it was in bounds — replayable before any policy change ships.

📊

Per-Engineer Usage & Cost Tracking

Token and dollar spend attributed per engineer, per model, per call — not just an aggregate bill. Rolling budget windows with automatic reset, not a cap that silently locks people out forever.

⚖

Model & Reasoning-Tier Routing

Route by intent, not just by model name — a "planning" alias gets extended-thinking depth on the same efficient model, while cost and requested-intent stay separately tracked in every log line. Automatic failover across backends keeps agents dispatching through a provider outage or rate limit.

💬

Slack-Native Coding Agents

Purpose-scoped dev/QA/DevOps agents that live in a Slack channel — no API keys, no local config. Ask a question or hand off a task like talking to a teammate.

🔐

IDE Proxy for Coding Assistants

A governed proxy in front of your coding-assistant traffic — per-engineer keys, budget enforcement, and automatic account failover, so IDE AI usage is visible and controllable, not a black box.

Thrasoz Product Family

Four products. One operating system.

SLA Guardian

—

Orchestra uptime compliance

Migration Commander

—

Client migrations in progress

Compliance Tracker

—

Governance audit status

AI Insights

—

Total orchestra spend

Transformation Score

—

AI Workforce Readiness

Tenant Mode

Operational

Recent Activity Last 24h

Spec Status Distribution

Build Pipeline

Template Tags

🏆 Token Leaderboard

Slack watcher conversations

Automation Operations

🛡 Breakfix Scanner

Click to run

⚙ Fleet Optimizer

Click to run

✅ SLA Guardian

Click to run

Fleet Health — SF + LMI + Snowflake

Active Agents

refreshing every 15s

NR Noise rate

Silent drops

Open exposure

SLA at risk

Repeat offenders

NR storms

1. Ghost Analysis — gap between cases and reality

Cases without a matching outage in Snowflake → false alarms (NR over-firing). Outages without a matching case → silent drops nobody worked.

2. True MTTR — case-grade vs business-grade recovery time

Case-grade MTTR = SF created→closed. Business-grade MTTR = kiosk back online (Snowflake) → case closed (SF). The gap reveals queue lag.

3. Owner × $ Exposure — who's holding the most active loss

Open kiosk cases × estimated revenue lost from corresponding offline LMI host. Workload imbalance shown in dollars, not counts.

4. Repeat Offender Cases — hardware swap candidates

Same kiosk, ≥3 cases in 30d. Likely hardware fault or runbook gap. Worth ops review or vendor escalation.

5. NR Storm Post-mortem — silent fleet event detector

When ≥3 identical SF subjects fire in 30 min, count LMI offline transitions in same window. If LMI dropped 50 hosts but only 5 cases opened — silent fleet event upstream of NR.

6. SLA At Risk — predictive escalation queue

High-priority open cases > threshold age, kiosk still offline in LMI, no recent owner activity. Risk score = age × idle factor × (kiosk-still-down boost).

7. Brand / Region Heatmap — PE-grade comparator

Per-region case rate, store coverage, MTTR, and outage count. Surfaces if Germany is 3× the US rate, or if BK_CA cases dwarf actual outages.

Musician Directory

🕐 Historical

Musician Name

Musician Type

Overview

Personality & Context

Collaboration

Workflow

Rules & Guardrails

Tools & Integrations

Performance

SHIPYARD

Processing Efficiency

92%

Decision Accuracy

88%

System Status

Operational

Last updated: just now

Describe how this musician should sound and think like your team

Knowledge-Base Upload

Upload files to enhance the musician's knowledge base. Supported: PDF, DOCX, TXT

Your safe space to teach, co-create, and collaborate with AI — side by side.

You (Department Head)

Subject Matter Expert

📂 Drag & drop documents, notes, or SOPs here to share knowledge

Your AI Partner

Learning from your expertise

AI RESPONSE

I'm ready to learn from your expertise. Share your processes, decision criteria, and edge cases — I'll incorporate them into how this musician thinks and operates.

SUGGESTION

Based on similar musicians in your orchestra, consider adding escalation rules for high-value transactions. Want me to draft those?

Knowledge Transfer Progress

✓ Domain context shared

✓ Core processes defined

○ Edge cases pending

○ Validation rules needed

Workflow & Orchestration

▶ Start

→

📄 Receive Input

→

⚙ Process Data

→

✓ Validate

→

🚀 Execute Action

→

📊 Report

→

■ End

Drag nodes to reorder

⚡ AI Suggestions

Consider adding an error handling step after Validate

Add retry logic for Execute Action failures

A notification step before End would improve visibility

🔧 Step Configuration

Select a step to configure its behavior

Timeout: 30 seconds

Retries: 3

On Failure: Escalate

Rule Builder

In your own words, describe the rule you want to create

Examples

Reject orders with less than 20% profit margin

Flag orders exceeding $500 for manager approval

Tools & Integrations

Connect your tools and integrations to enhance musician functionality.

HubSpot

CRM integration

Connected

Stripe

Payment processing

Pending

GitHub

Code repositories

Connected

Jira

Project tracking

Connected

Slack

Team communication

Connected

Analytics

Business intelligence

Not Connected

Success Rate

98.7%

▲ 2.3% from last month

Avg Response Time

—

▼ 15ms improvement

Tasks Completed

1,247

Last 30 days

Processing Times (last 7 days)

MonTueWedThuFriSatSun

Task Distribution

Completed1,230

In Progress12

Failed5

Partnership Highlights

✓ 99.9% uptime in Q1 2026

✓ Reduced processing time by 40%

✓ Handled 1M+ orders seamlessly

✓ Zero security incidents

Musician ID: —

Status: Active

Environment: Production

Deployment Pipeline

Source Code

→

Build

→

Test

→

Deploy

Build History

02:3m Build #1245 — SUCCESS

92:3m Build #1244 — FAILED

ID	Project	Type	Description	Status	Priority	Created	Actions

🧾 Invoice Reconciliation

Upload invoices, QuickBooks exports, PSV order data, or PDFs. AI cross-references sources and flags discrepancies by enrollment.

🔍

AI Search

Task Description Context (Help MAESTRO create a better template)

1 Functional Area

2 Pick Template

3 Describe It

4 Review & Send

What functional area is this musician for?

Knowledge work, software development, or anything in between.

💰

Finance

Invoicing, billing, cost tracking

👥

Onboarding, reviews, workforce

📞

Contact Center

Tickets, calls, customer support

💻

Software Dev

Code, testing, deployments

⚙

Operations

Monitoring, infra, SRE

⚖

Legal

Compliance, contracts, policy

📣

Marketing

Campaigns, analytics, content

🔒

Security

Audits, pen-testing, access

📈

Sales

Pipeline, CRM, forecasting

📑

Accounting

GL, reconciliation, close

🏦

Tax

Compliance, filing, nexus

🤝

Account Mgmt

Client success, renewals

🎨

Custom

Something else entirely

Total Pipelines

—

Running

—

Completed

—

ID	Task	Status	Org	Created

Audit Log

Time	Action	Resource	User	Details

—

Programs

—

Total Rules

—

Currencies

Source

Lighthouse (accounting.tillster.com) — extracted via Playwright

Title	Status	Priority	Assignee	Created

Conductor

Full access to all products and functional areas

Signals: Yes | Maestro: Yes | Shipyard: Yes

Section Lead

Scoped to functional area(s). E.g., Chris → HR

Signals: No | Maestro: Yes | Shipyard: Yes

Player

Access to specific musicians only

Signals: No | Maestro: Yes | Shipyard: Yes

Username	Display Name	Email	Role	Tenant	Signals	Maestro	Shipyard	Status	Actions

Filters

Loading overview...

Filters

Employee	Department	Action	Reason	Status	Initiated	Actions
Loading...

Employee	Action	Outcome	By	Date
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Queue Health by Project

Hot Alerts

Musician Status Grid

7-day spend

—

USD

7-day interactions

—

Bot calls

Lifetime spend

—

USD, all time

Lifetime tokens

—

Total tokens used

Daily spend by model (last 7 days)

Interactions (last 7 days)

Hide interactions under $1

Time (UTC)	Model	Source	Tokens	Cost	Thread
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CLI / chat sessions (lifetime)

Source	Count	Last active (UTC)
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Every GitHub Auto-Review proxy key combined (self-serve, tce-ai, per-repo, per-engineer variants). "Interactions" below are individual API calls, not PR reviews - one review is several turns (read diff, check conventions, post comment), so there is no 1:1 review count yet.

Lifetime spend

—

USD, all time

Lifetime interactions

—

Individual API calls

Avg $/interaction

—

Lifetime average

7-day spend

—

USD

Daily spend by repo (last 7 days)

By repo (lifetime) (click a repo for its full call history)

Repo	Calls	Cost	Avg $/call
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Recent interactions (most recent 300 calls across all repos - click a repo above for one repo's full history)

Time (UTC)	Repo	Model	Tokens	Cost
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7-day spend

—

USD, all people, last 7 days

7-day interactions

—

Interactions this week

People active

—

Distinct people, last 7 days

Daily spend by person (last 7 days)

Spend by person

Person	Interactions	Tokens	Total cost	Last active (UTC)
Loading…

Engineer Keys

—

active proxy keys

Total Weekly Spend

—

sum across all active keys

Slack Agents

—

musicians configured

Proxy Keys & Budgets

show revoked

Engineer	Email	Department	Supervisor	Budget	Spend	Remaining	Resets	Status
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Slack-Native Agents

Agent	Tenant	Workspace	Channel	Model	Effort	Allowed Users	Last Run	Enabled
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Musician Permissions & Scope DB-backed, live within ~30s — no restart needed

Musician	Allowed Users	Denied Users	Model	Effort	Last Updated
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AI-Authored PR Outcomes factual record, no score yet — human review below

PR	Agent	Requested By	State	Time to Merge	Review Comments	Reverted?	Notes
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Usage by Person (all-time)

Person	Calls	Tokens	Cost
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Usage by Model

Model alias	Calls	Tokens	Cost
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Usage by Surface

Surface	Calls	Tokens	Cost
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Resolution by Status

Volume Trend

Top Projects by Volume

Revenue Impact

—

Intelligence Score

—

Open Findings

—

Tagging Coverage

—

Est. Savings

Severity	Type	Resource	Description	Account	Status	Action

Systems Leaderboard

AWS Cost Analysis

—

Total Spend (MTD)

—

MoM Change

—

Top Service

Name	Spend	% of Total	Share
Loading...

Classification Coverage

—

Total Resources

—

Classified

—

Coverage %

Cost by Product

Cost by Owner

Bulk Classify Untagged Resources

	Resource ID	Type	Account	Region	Finding
Click "Load Untagged" to fetch resources needing classification

—

Total Findings

—

Verified Live

—

Critical

—

Files Affected

—

Commits w/ Secrets

Severity	Verified	Type	File	Commit	Author	Secret	Action
No scan results yet — click Run Scan to start

—

Health Score

—

P1 Incidents

—

P2 Incidents

—

Degraded Apps

—

Critical Hosts

Open Incidents

Severity	Title	Entity	Duration	Details	Action
Run a check to see current incidents

Application Health

Infrastructure

Order Failure Analyst

—

Total Orders

—

Successful

—

Failed

—

Failure Rate

—

Stores Affected

—

Failure Types

Failures by Category

Category	Count	Stores	Tenants
Click "Analyze" to scan for failed orders

Top Errors

Error Message	Count	Category
—

Most Affected Stores

Store	Tenant	Failures
—

App Error Rates

Application	Error Rate	Errors
—

—

Total Velocity

—

Committed

—

Completion %

—

Carry-Over

—

Blocked

—

Headcount

—

Capacity %

—

Available Hours

—

Predicted Velocity

—

Recommended Commit

ACP — Agentic Commerce Protocol

LIVE

GPT-4, Gemini, all major AI agents

UCP — Universal Commerce Protocol

PENDING

Google waitlist submitted 2026-04-15

POS Adapter (BSP)

MOCK

Flip to sandbox once adapter creds are wired

—

Enrolled Merchants

—

Orders Today

—

Revenue Today

—

Active Sessions

Merchant	POS Provider	Rate Limit	AI Actions	Status	Enrolled
Loading...

Order ID	Site	Customer	Total	ETA	Status	Time
No orders yet. Place an order via Harmony commerce mode.

🚚 Merchant Delivery Preferences

Thrasoz Demo Kitchen

site-001 · No preferred provider

Auto-Compare

Thrasoz Express

site-002 · Preferred: DoorDash Drive

DD Preferred

Merchants with a preferred provider skip the multi-provider comparison. Harmony routes directly, cutting 1-2 tool calls from the conversation.

📊 Live Fulfillment Queue

NCR-DEMO-…-0001

DoorDash · 28 min DISPATCHED

NCR-DEMO-…-0002

Pickup · 18 min PREPARING

NCR-DEMO-…-0003

Grubhub · 35 min ENROUTE

🌟 Intelligent Scoring — Last Comparison

DoorDash Drive

RECOMMENDED

Total Fees

$13.49

ETA

28 min

Grade

⭐ 4.8

Time: 0.200 Cost: 0.164 Grade: 0.240 Score: 0.604

Grubhub

Total Fees

$11.98

ETA

35 min

Grade

⭐ 4.6

Time: 0.087 Cost: 0.252 Grade: 0.230 Score: 0.568

Scoring weights: Time 40% · Cost 35% · Reliability Grade 25% · Min grade threshold: 4.5 · Both providers qualify

87%

Delivery Success Rate

28.4

Avg ETA (min)

$12.74

Avg Delivery Fees

4.72

Avg Provider Grade

Provider Adoption

DoorDash Drive54%

Grubhub28%

Pickup (self)18%

DoorDash wins 54% of head-to-head comparisons on speed + grade. Grubhub wins when total cost is the primary factor.

Intelligent Routing vs. Manual

AI-Scored Selections 82%

Merchant-Preferred (skip compare) 11%

User Override (chose non-recommended) 7%

💡 AI recommendation accepted 93% of the time when comparison is shown.

🔗 NCR Partner Intelligence

NCR Sites Enrolled

Both AI-enabled

Sites with Preferred Provider

Thrasoz Express → DoorDash

100%

Tracking Synced to NCR

Live tracking_url in every order

💡 NCR Insight: 1 site has no preferred provider configured. Configuring a default provider for Thrasoz Demo Kitchen would reduce per-order tool calls by 33% (skip compare_delivery_providers). Recommend setting DoorDash as default given 54% win rate.

+34%

Discovery Lift

$1.22

Avg Routing Savings

Disputes Auto-Routed

Harmony Sessions

Delivery Routing Breakdown

NCR (Default) 61%

DoorDash Drive (Least-Cost) 28%

Square (Explicit) 11%

Least-cost routing saved customers an average of $1.22 per order vs default routing.

Dispute Auto-Routing

→ Store 7 resolved

→ Delivery Partner 5 resolved

Avg Resolution 19h

100% auto-routed by NLP keyword inference. 0 manual escalations required.

🌐 Discovery Intelligence — Top Queries

"burger near me"

34 queries · 2.1 avg results

"cheap ramen"

28 queries · 1.8 avg results

"coffee open now"

22 queries · 1.2 avg results

"healthy bowls"

18 queries · 0.9 avg results

"best pizza"

15 queries · 1.4 avg results

💡 Gap detected: "healthy bowls" has 0.9 avg results — only 1 enrolled location serves salads. Enrolling more health-focused merchants would capture ~18 unserved queries/week.

🎧 Harmony Full-Lifecycle Funnel

Sessions Started

Discovery Searches

Carts Built

Orders Placed

Disputes Filed

51% session-to-order conversion · 50% dispute auto-resolution rate

$262.7M

Portfolio Revenue

89 locations · 6 brands

$41.9M

Portfolio EBITDA

15.9% margin · +11.3% YoY

1.5x

Blended MOIC

Target: 2.5x · 16.5% IRR

$268M

Dry Powder

$412M deployed of $680M committed

SELECT PORTCO:

Apex Logistics

Food Service · 42 stores · 3 brands

EXIT READY

$127.4M

Revenue

$18.9M

EBITDA · 14.8%

1.7x

MOIC · 19.2% IRR

3.2 yrs

Hold · Entry Q4 2022

SSS +4.2% · Digital 31% · Exit window 2027 · Buyers: Sysco, KKR, Roark

🔗 Paste Link

Last generated: Q1 2026 (pre-loaded)

NovaMed Health

Urgent Care · 28 locations · 2 brands

18 MO RUNWAY

$84.1M

Revenue

$15.6M

EBITDA · 18.5%

1.4x

MOIC · 16.8% IRR

2.1 yrs

Hold · Entry Q1 2024

SSS +7.1% · IT cleanup req · SOC 2 gap · Buyers: HCA, TeamHealth, Optum

🔗 Paste Link

Last generated: Q1 2026 (pre-loaded)

Redwood Industrials

Manufacturing / Food Service · 19 sites · 1 brand

EXTEND HOLD

$51.2M

Revenue

$7.4M

EBITDA · 14.5%

1.2x

MOIC · 13.4% IRR

1.4 yrs

Hold · Entry Q4 2024

SSS +2.8% · PCI non-compliant · $0 IT budget · Buyers: Compass, Aramark

🔗 Paste Link

Last generated: Q1 2026 (pre-loaded)

Fund III Portfolio Roll-Up

LP Reporting Summary · Q1 2026

ALL PORTCOS

Metric

Target

Actual

Gross MOIC

2.5x

1.5x

Net IRR

22%

16.5%

Digital Mix

35%+

17% avg

SSS Growth

4.2–7.1%

Exit Ready

Apex '27

🔗 Paste Link

Last generated: Q1 2026 (pre-loaded)

Tillster, Inc.

Live PE Report · Source: Signals GL · MA-97

LIVE DATA

Pulls /api/portco/overview, /operations, /covenants from Signals and renders a PE-grade deck: KPIs, EBITDA waterfall, covenants, liquidity, risk register, exit-readiness, 6-mo forecast.
Requires GL data uploaded to Signals for tenant tillster.

Built on-demand from Signals

🔗 Shareable PDF Links (Shipyard Paste)

Click to open · right-click to copy URL

Apex Logistics — Q1 2026

Apex_Logistics_Q1_2026.pdf

Open ↗

NovaMed Health — Q1 2026

NovaMed_Health_Q1_2026.pdf

Open ↗

Redwood Industrials — Q1 2026

Redwood_Industrials_Q1_2026.pdf

Open ↗

Fund III Portfolio Roll-Up — Q1 2026

SilverLake_Fund_III_Portfolio_Q1_2026.pdf

Open ↗

Musicians

Order Failure Analyst

SRE Monitor & Incident Response

Revenue Lifecycle Auditor

Collections Tracker

Secret Scanner

Sprint Metrics

Capacity Planner

Contract Reconciler

Intercompany Reconciler

Automated Code Review

Self-Service Agent Creation

Platform

RBAC + Multi-Tenant

Automated Reports

Knowledge Base

Cloud Intelligence

Shipyard Integration

Harmony Voice

SIGHT — Living Requirements

Config Drift Watch

AI Governance & Tracking

Typed Agent Scopes

Hash-Chained Audit Trail

Per-Engineer Usage & Cost Tracking

Model & Reasoning-Tier Routing

Slack-Native Coding Agents

IDE Proxy for Coding Assistants

Thrasoz Product Family

Signals

Harbor

DryDock

🏆 Token Leaderboard

Automation Operations

Fleet Health — SF + LMI + Snowflake

🧾 Invoice Reconciliation

Interactions (last 7 days)

CLI / chat sessions (lifetime)

Personal Claude Code usage (lifetime)

Org chain — 7-day spend

By repo (lifetime) (click a repo for its full call history)

Recent interactions (most recent 300 calls across all repos - click a repo above for one repo's full history)

Spend by person

Proxy Keys & Budgets

Slack-Native Agents

Musician Permissions & Scope DB-backed, live within ~30s — no restart needed

AI-Authored PR Outcomes factual record, no score yet — human review below

Usage by Person (all-time)

Usage by Model

Usage by Surface

Systems Leaderboard

AWS Cost Analysis

Classification Coverage

Bulk Classify Untagged Resources

Recommendations

Findings by Category

Open Incidents

Application Health

Infrastructure

Recommendations

Failures by Category

Top Errors

Most Affected Stores

App Error Rates

🔧 Fix Suggestions (Knowledge Base)

Recommendations

📧 Send Order Failure Report

📚 Order Failure Knowledge Base

Recommendations

Recommendations

🖂 Omnichannel Inbox

📋 Review Board

🌎 Social Monitor

🎵 Harmony — FlexBets Support