Arcovo AI
Operational Efficiency & AI Adoption Audit
Our response to your RFP, and how we'd make SREG the most efficient mall operator it can be.
What we heard from your RFP and our call with Camillo and Caitlin
Margins are getting squeezed
Fee schedules are flat while payroll and operating costs keep rising. Revenue and efficiency are the two levers, and this engagement pulls the second one.
The portfolio moves fast
About 10 malls to about 50 in six years, with closer to 80 brought on and 30 transitioned out. Every transition in or out is real work for your team.
Phase two raises the stakes
Joint ventures and owned assets with your PE partner mean more properties. Growth can't mean headcount growing in step.
Security is now a contract requirement
Grand Central and the MTA mean SOC 2. Anything we do has to help that effort, not complicate it.
Audit against your goals
You'll share 12, 24 and 36 month goals and a growth scenario. That's the yardstick, not efficiency for its own sake.
The 140-item list is a starting point
It's one internal view, from small fixes to reporting requests. Your processes aren't broken. They could be faster, and we'll validate that with our own conversations.
And AI won't always be the answer. Sometimes it's a process fix or a feature you already pay for. A good audit says so.
Map the whole company first. Then go deep, one department at a time.
Weeks 1 to 3
Strategy Mapping
High-level conversations with leadership and all nine department heads. Output: your AI Strategy Roadmap, with the best use cases to start with.
Weeks 3 to 6
AI Workforce Consultation
Our standard process, run hundreds of times. Deep dives on the first department, then the AI Workforce Blueprint in week 6.
Week 7 on
Build, while the next AWC starts
Implementation kicks off, and the AWC on the next use case from the roadmap starts at the same time.
A rolling process: one department in build, the next in discovery
First department
AWC
Build and go-live
Next department
AWC
Build and go-live
The one after
AWC
Build
No multi-year lock-in. You decide department by department, and we earn the next one.
01
Why Arcovo
Operators who build, a process we've run hundreds of times, and a team that's down the street.
We've scaled a company through the same pressures you're facing
8-figure
exit when Jeff and Jake sold Digital Hyve in 2021, with every employee becoming an owner through an ESOP
#0
on the Inc. 5000, after scaling Digital Hyve to multiple locations
Pre-AI
We scaled it without any of the tools we build now, and we know how much more we could have done with them.
Most technology people aren't operators. We're both.
We lived the payroll pressure, the hiring bottlenecks and the processes that only worked because someone stayed late. That's why we start with how the business runs, not with the technology.
After Digital Hyve, Jeff co-founded multiple businesses and restaurants, has invested in 13+ companies, and sits on the board of Community Financial System, a publicly traded top-100 bank and financial services company. Jake runs Arcovo's delivery and operations as COO.
Arcovo AI designs, builds and runs AI Employees
Each AI Employee takes over a defined responsibility, works inside the systems you already use, and we host and maintain it for as long as you use it.
0+
AI implementations for SMB and middle-market companies, including PE portfolio companies
Practice areas
Strategy, the AI Workforce Consultation, implementation, and ongoing hosting, support and maintenance.
Based in Syracuse
The Inspyre building, downtown. Most of the team on this engagement is a short drive from your office.
Industries
Professional services, home and field services, manufacturing and distribution, healthcare and nonprofits, hospitality, associations, financial services, government contractors, media and real estate.
Some of the companies we work with
0+
AI implementations
The firm that audits should be the firm that builds
Camillo, you told us most firms you've talked to are either business consultants or AI shops. We think that split is the problem. It's hard to recommend tooling with confidence unless you're building with it every week, because what works changes month to month.
We learned this the hard way
We started on a popular agent orchestration platform. It worked fine until we needed an agent to read and analyze a 350-page document, and the platform couldn't handle the run time. So we went fully code-native on our own platform, Nova.
What Nova means for you
Nova packages years of our build patterns, integrations and testing, so new AI Employees start from proven parts and our engineers direct AI coding agents inside it. That's how custom work stays fast and affordable, with no lock-in to a no-code tool.
The recommendations in your roadmap will come from the people who'd be accountable for building them. And if a tool you already own is the better answer, we'll tell you.
02
How we'd work together
Strategy Mapping, the AI Workforce Consultation and the blueprint, mapped to every part of your RFP.
How the engagement runs
Wk 1
Wk 2
Wk 3
Wk 4
Wk 5
Wk 6
Wk 7
Wk 8
Wk 9
Wk 10+
Strategy Mapping
Leadership and department heads
AWC deep dives
First department, recorded
Blueprint
Present
Implementation
Kickoff, access, build, test, go-live
Next AWC
Next use case from the roadmap
Weeks 1 to 3
Strategy Mapping. High-level interviews with leadership and each department head. Output: your AI Strategy Roadmap.
Weeks 3 to 5
The AI Workforce Consultation on the first department. Recorded deep dives and process mapping.
Week 6
Blueprint presentation, in person. The AWC is complete and you decide what to build.
Week 7 on
Implementation kicks off, and the next AWC starts at the same time. Six weeks to a blueprint, longer if you build.
Strategy Mapping, weeks 1 to 3
What happens
A leadership session, in person, on your 12, 24 and 36 month goals and the growth scenario.
High-level interviews with the head of each of the nine functions, plus 1 to 2 people from their team. We're looking for where the work is, where it grows with property count, and where it hurts.
A review of your 140-item list and existing documentation, used as input, not a substitute for talking to people.
What you get: your AI Strategy Roadmap
The best use cases across the company, ranked by value against effort and sequenced by dependency.
A recommendation on which department and use case to start with, and why.
Our point of view on buy vs. build for each use case, plus the governance model and starting AI usage policy.
A readout with your leadership team at the end of week 3.
This is where your RFP's company-wide audit happens. It covers all nine functions without making you pay for nine deep dives before you know where the value is.
The AI Workforce Consultation: the process we've run hundreds of times
1. Kickoff
In person. We agree on the system or process we're going after, who needs to be in the deep dives, and the schedule.
2. Deep dives
Virtual and recorded. Your people share their screens and walk us through the work, start to finish: every system, click, handoff and exception.
3. Process mapping
We map everything we heard into a current-state process, then design the future state with AI Employees and humans in the loop.
4. Blueprint presentation
In person. Findings, recommended AI Employees, the impact, timeline and total investment.
How we run a deep dive
We treat it like we're hiring someone to do the job and our AI Solutions Architect is the new hire. You share your people, process, systems and workflows. The department head and the people who actually do the work, typically 3 to 5, show us exactly how it gets done today, including the workarounds nobody wrote down.
Every session is recorded, so we capture each screen and button click and nothing depends on someone's notes. The recordings feed straight into process mapping and the blueprint.
Strategy sessions and presentations happen in person at your office. Deep dives stay virtual because we need to record screens.
What the AI Workforce Blueprint gives you
A 15 to 25 page document that shows exactly where automation can be built and where your people stay in the loop. It covers your current state with a process map, the recommended future state with a process map, a spec for each AI Employee, the technical architecture and integrations, the implementation plan and timeline, the business case in your own numbers, success metrics and next steps.
How a future-state map reads (illustrative example)
AI EmployeeA new lease arrives for a property being transitioned in.
AI EmployeeReads it and abstracts rent schedule, CAM terms, options and co-tenancy.
AI EmployeeFlags anything unusual against your standards.
Human in the loopLease admin reviews the flagged items and approves.
AI EmployeeStages the data for Yardi and logs what it did.
AI Employee does the workA person decides
The current-state analysis also rates each workflow on efficiency, scalability under your growth scenario and automation feasibility, the three dimensions your RFP asks for.
How the blueprint decides what gets built
Recommended
Clear value in your numbers, a reachable integration path and a build we can quote with confidence. These get a full spec, price and timeline.
Phase two
Valuable, but it depends on something else landing first, like clean lease data before CAM reconciliation. Sequenced on the roadmap.
Not recommended
The cost outweighs the value, or the better answer is a process fix or a feature you already own. We say so in writing.
What we weigh for every AI Employee
Value measured in your volumes, time and cost. Build effort and calendar from the technical spec. The integration path into Yardi, Power BI and Microsoft 365. Where a person has to stay in the loop. What it depends on.
A real example
In a recent blueprint for a telecom provider, we recommended two AI Employees, held a third for phase two, and advised against a fourth because it wasn't worth building yet.
How we avoid a product in search of a problem
Your goals come first
Every use case on the roadmap traces back to one of your 12, 24 or 36 month goals or the growth scenario. If it doesn't, it's not on the roadmap.
Value gets measured in your numbers
Your volumes, times and costs from the deep dives. No generic "hours saved" claims.
Fix the process before automating it
Automating a broken process just gets you to the wrong answer faster. Half of this work is process optimization.
Buying and doing nothing are real options
If Yardi, Power BI or Microsoft 365 already does it, we'll say so, even though we don't get paid to build it.
The people doing the work sign off
Future-state designs get checked by the person doing the job today, not just their manager.
We don't come in with a catalog
We've built the same kinds of solutions many times, which makes us faster. It doesn't decide what your roadmap says.
All nine functions, with hypotheses to test
| Function | What we'll look at (from the RFP) | Early hypotheses, not conclusions |
|---|---|---|
| Leasing | Deal pipeline, pitch and proposal development, LOI-to-lease, comp data | Proposal and LOI drafting, comp pulls, pipeline updates |
| Specialty leasing | Short-term deals, license agreements, coordinator workflows | License agreement generation, expiration and renewal tracking |
| Lease admin and property transition | Lease abstraction, Yardi data entry, transition in and out | Lease abstraction staged for Yardi, transition checklists, data validation |
| Property management and operations | Daily operations, vendor management, facilities | Vendor invoice and insurance certificate tracking, work order triage |
| Marketing and tenant relations | Collateral and renderings, sponsorship, tenant communications | Tenant communication drafts, sponsorship tracking |
| Accounting and financial reporting | AP and AR, CAM reconciliation, ownership package, close | AP matching, CAM reconciliation prep, ownership package commentary |
| Construction and tenant coordination | Tenant build-out coordination, construction draws | Draw package assembly, build-out document tracking |
| Business intelligence, data and IT | Yardi environment, Power BI, data architecture, systems outside Yardi | Yardi data quality checks, self-serve reporting requests |
| Human resources | Recruiting, onboarding, administration | Onboarding packets, recruiting coordination, policy questions |
Where to start is the first thing Strategy Mapping answers
We'd rather earn the right to recommend a starting point than guess at one today. Camillo shared good arguments for two candidates, and Strategy Mapping is how we'll pick between them with real information.
Lease administration and property transition
Tied to your recurring property management fee. With 80 malls brought on and 30 transitioned out in six years, this work grows directly with property count, and clean lease data pays off downstream in CAM and ownership reporting.
Leasing
The biggest upside per deal. Faster proposals, LOIs and comps mean more deals per leasing rep, but new-deal commissions swing with the market cycle.
What we'll weigh: value in your numbers, how much the work grows with property count, data readiness in Yardi, the integration path, and your team's appetite to change how they work.
What you get, mapped to Section 5 of your RFP
| Your RFP asks for | Where it lives in our process | When |
|---|---|---|
| Kickoff workplan and interview schedule | Strategy Mapping kickoff: week-by-week plan, named interviewees, in-person sessions | Week 1 |
| Consolidated, prioritized opportunity register | The AI Strategy Roadmap: use cases across all nine functions, ranked by value against effort and sequenced | Week 3 |
| Organization and governance recommendation | Delivered with the roadmap: support model, starter AI usage policy and recommended roles | Week 3 |
| Department findings memo | The AI Workforce Blueprint's current-state analysis, with process maps of every workflow we covered | Week 6 |
| Implementation roadmap | The blueprint's future state, AI Employee specs, architecture, buy-vs-build view, implementation plan and timeline | Week 6 |
| Executive presentation | The roadmap readout in week 3 and the blueprint presentation in week 6, both in person with your leadership team | Weeks 3 and 6 |
One difference from a typical audit: the blueprint is ready to build. It includes a fixed implementation price and timeline, so the week you approve it, we start.
03
Doing it responsibly
Buy vs. build, your AI control center, governance, your AI usage policy and how we protect your data.
You don't want to build and maintain software. You shouldn't have to.
Use what you own
Features in Yardi, Power BI and Microsoft 365 you're already paying for. Cheapest answer when it fits, and the first thing we check.
Buy a platform
Category-level recommendations for packaged software where the market already solves it well. We stay vendor-neutral.
Arcovo builds and runs it
Custom AI Employees that work across Yardi, email, documents and Power BI where packaged tools leave gaps. We host, monitor and maintain them. You own the IP. Your team never builds or babysits software.
We build software, so here's how we keep ourselves honest: anywhere we recommend a build, the roadmap shows the buy option and its cost right next to it.
Your AI control center, built for SREG
A custom operating system that sits next to Yardi, Power BI and Microsoft 365. Your team logs in with role-based permissions and runs your whole AI strategy from one place, in your brand.
- Manage your AI EmployeesAssign work, set rules and switch them on by property.
- See what they're doingLive activity across every mall and department.
- Make the decisions that matterAnything that needs a person lands in one queue.
- Every output in one placeAbstracts, workpapers and drafts, searchable and logged.
- Role-based accessLeadership sees the portfolio. A GM sees their mall.
Concept mockup. AI Employees, tenants and figures are illustrative.
ai.spinosoreg.com/control-center
AI Control CenterAll properties
EXExecutive leadership
Executive leadershipFull portfolio, every AI Employee
Lease administrationLease decisions, all properties
Property GM, Solano Town CenterOne property only
Viewing as Property GM. You see Solano Town Center only.
Good morningUpdated just now
Tasks completed this week1,284
Waiting on a decision3
Leases abstracted142
Exceptions flagged9
PropertiesAI Employee activity
White Marsh Mall3 active
The Mall at Fairfield Commons2 active
Solano Town Center3 active
Gadsden Mall1 active
Work completedLast 7 days
ThuFriSatSunMonTueWed
AI Employees4 working for SREG
L
LenaLease abstraction, Lease Admin
Working
Fairfield Commons transition: 38 of 112 leases abstracted
C
CamCAM reconciliation prep, Accounting
Working
Gadsden Mall 2026 reconciliation workpapers
S
SashaLicense agreements, Specialty Leasing
Waiting on you
2 holiday kiosk agreements ready for review
O
OwenOwnership reporting, Accounting
Scheduled
September ownership packages, due in 4 days
Live activityAll properties
Decisions waiting on you3 open
Co-tenancy clause differs from your standardLena
Northpoint Outfitters, Suite 1120, Solano Town Center. Lena drafted the abstract and highlighted the clause.ApproveEditSend back
CAM cap exceeded for 3 tenantsCam
White Marsh Mall. Cam calculated the overage and needs a call on how to bill it.ReviewAssign
Holiday kiosk license, 90 daysSasha
Solano Town Center. Standard terms, ready to send for signature.ApproveEdit
OutputsEvery file, logged and searchable
| Output | Property | By | When |
|---|---|---|---|
| Lease abstract, Suite 1120 | Solano Town Center | Lena | 2 min ago |
| CAM workpaper, 2026 | Gadsden Mall | Cam | 1 hr ago |
| License agreement, holiday kiosk | Solano Town Center | Sasha | 3 hr ago |
| Variance commentary, September | Fairfield Commons | Owen | Yesterday |
| Lease abstract, Suite 214 | White Marsh Mall | Lena | Yesterday |
AccessRole-based permissions
| Role | Properties | AI Employees | Decisions | Outputs |
|---|---|---|---|---|
| Executive leadership | All | Manage | All | All |
| Lease administration | All | Lena only | Lease | Lease |
| Accounting | All | Cam, Owen | CAM, reporting | Finance |
| Property GM | Own mall | View | Own mall | Own mall |
Approved. Logged to the audit trail.
Our view on governance: a small hub, a champion in every department
The hub
Owns AI policy, tool and vendor approvals, data access, the roadmap and how results are measured. Small: one program lead plus support. Natural home: Caitlin's business intelligence and process improvement team.
The spokes
One champion per department, from existing staff, part-time. They know the work, bring ideas forward, test outputs and own adoption with their peers.
Why not a pure center of excellence?
It turns into a bottleneck and drifts away from how the work actually gets done in each department.
Why not champions alone?
Tools multiply, data rules vary by department, and spend duplicates. That's a SOC 2 problem waiting to happen.
Recommended roles: an AI Program Lead (likely an expansion of an existing role), department champions, and an executive sponsor at the leadership table, Don as COO.
A starting AI usage policy and data governance framework
Approved tools
Company accounts only. No company data in personal AI accounts.
Data classes
Financial, tenant, personnel and public-sector contract data, each with rules on which tools can touch it.
No training on your data
Vendor terms must rule out model training and limit data retention.
Human review
Anything going to a tenant, owner, lender or employee gets reviewed by a person until it earns otherwise.
Least-privilege access
AI Employees get only the data they need, and their actions are logged.
New-tool intake
A light review before any new AI tool is adopted. Maps to SOC 2 vendor management.
Incidents
Who to tell, how fast, and what happens next.
Training
What staff can and can't do, in plain language.
We'd write it alongside your SOC 2 controls, so your team is following one set of rules, not two.
Data security and confidentiality
Your NDA
Yes. We'll sign SREG's mutual NDA before we receive any documentation, data or access.
Least privilege
We ask for access to the specific documents and data an AI Employee needs. Never full-system access.
Isolation
Your data and environment stay isolated. Never commingled with other clients' data, never used to train a model.
Platforms
The platforms we build on are SOC 2 Type 2 compliant and ISO certified.
Credentials
Through approved secure methods and permissioned accounts, never over email or chat. Test environments wherever they're available.
Sensitive data experience
We've built around HIPAA-protected health data, CUI for government contractors, financial records and student data.
The MTA contract and your SOC 2 effort
Anything touching Grand Central data gets its own architecture and vendor-terms review before we go near it. We'll also help with your SOC 2 effort where it's useful.
04
Team, proof and investment
Who does the work, who you can call, and what it costs.
The people who pitch it are the people who do it
| Name | Role on this engagement | Seniority and background |
|---|---|---|
| Jeff Knauss | Executive sponsor | CEO and Co-Founder. Co-founded, scaled and sold Digital Hyve. |
| Jake Tanner | Methodology and quality oversight | COO and Co-Founder. Co-founded, scaled and sold Digital Hyve. |
| Sarah Forrest | Engagement lead: runs Strategy Mapping, the deep dives and the blueprint | AI Solutions Architect. Runs every Arcovo consultation. |
| Chris Hayes | Technical architecture, buy-vs-build calls, Yardi integration path | CTO. Former technology leader at Kohl's, CIO at Stickley, technology leader at Siemens. |
| Michael Virnoche | Security, data governance, AI usage policy, SOC 2 support | Leads platform engineering and security. More than a decade leading security at IBM. |
| AI Solutions Manager | Implementation lead from kickoff through go-live and after | Assigned at build |
| Engineering team | Build, test and deploy the AI Employees | AI Solution Engineers, assigned at build |
Sarah leads every session herself. Jeff and Chris stay engaged through the blueprint presentation and into the build. Nothing gets handed to a junior team after the sale.
References you can call
Northland Communications
Jim McCarthy, President
315-671-6222
jmccarthy@northland.net
Engagement: An AI Workforce Consultation on network operations and an AI Employee that triages network alarms, identifies the affected customer and how critical they are, routes to the right team and creates the ticket. The on-call team still owns customer contact. A second AWC followed.
Mower
Erinn Steffen, Chief Operating Officer, Employee Owner
D 716-880-1409, M 703-371-8617
ESteffen@mower.com
Engagement: An AI Employee that assembles first-draft new business and RFP response decks from Mower's slide library, with a pitch lead making the strategic calls. They came back for a second AWC and build on accounts payable.
CGI / Hello Nation
Tom Doran, President and Chief Client Officer
585-450-2263
tdoran@cgicompany.com
Engagement: Four AWCs and two builds so far: quarterly business review preparation, client onboarding at CGI, and rebuilding the core software that manages their production calendars.
The RFP asks for at least two named contacts. We're giving three, each one a client that came back for more.
Our proposal: Option A, built to keep rolling
Strategy Mapping plus your first AWC
$9,500
Weeks 1 to 6. All nine functions mapped, the AI Strategy Roadmap, governance and policy, and the first department's deep dives and AI Workforce Blueprint.
Each AWC after that
$1,500
When you're ready to move on to the next department.
Implementation
Average$8.5K to $30K
A fixed fee per build, quoted in the blueprint. No hourly billing.
Monthly hosting and support
Average$1K to $3.5K
Per month. Covers technical support plus every token, credit, action, platform cost and tool your AI Employees use.
Why only Option A
We'd rather earn the next department than lock you into a company-wide fee up front. Strategy Mapping already covers all nine functions, so you get the company-wide view in three weeks without paying for nine deep dives.
What about B and C?
Option B happens naturally: each department after the first gets its own AWC at $1,500, at your pace. We aren't proposing Option C, because the value is in our team running the deep dives and building what we find.
How our pricing works
Implementation: a fixed price per build
On average $8,500 to $30,000, depending on how many AI Employees, how complex the integrations are and how many build weeks the technical spec calls for. It's quoted in the blueprint, so you know the number before you say yes. Typical payment terms: 50% at signature, the balance at each AI Employee's go-live.
Monthly: one flat fee, no usage surprises
On average $1,000 to $3,500 per month per build. Camillo asked what happens if token costs go up: within the agreed scope, that's ours to absorb. We size the fee from your expected volumes, and the few things that would change it, like a material jump in property count or a new capability, get named in the agreement before you sign.
Included every month
- Hosting and infrastructure
- AI models, tokens and credits
- Platform and tooling costs
- Monitoring and health checks
- Bug fixes and error resolution
- Minor adjustments
- Updates when platforms or models change
- Technical support
- Documentation
- Monthly check-ins
Priced separately, always quoted first
- New features and capabilities
- Additional AI Employees
- Scope expansions and process redesign
- Advanced analytics and reporting
Response within 24 hours, same day for critical issues, with continuous automated monitoring.
From today to your first AI Employee
Oct 9In-person presentation to SREG leadership
OctoberYour follow-up questions and diligence
Late Oct to early NovSelection and mutual NDA. You share goals, growth scenario and the 140-item list.
Weeks 1 to 3Strategy Mapping from the week of Nov 16. Roadmap readout the week of Nov 30.
Weeks 3 to 5AWC deep dives on the first department, into mid-December
Week 6Blueprint presentation, the week of Jan 4 after the holidays
Week 7 onImplementation kickoff and the next AWC, the week of Jan 11
Six weeks of working time from kickoff to a blueprint you can approve, and a rolling process from there.
Next steps
1
Send us your questions
Anything from today, and any diligence you need.
2
Execute the mutual NDA
So we can receive your goals, the growth scenario and the 140-item list.
3
Pick a kickoff week for Strategy Mapping
We'll have the workplan and interview schedule ready for week one.
Let's make SREG the most efficient mall operator in the country.
Jeff Knauss, CEO and Co-Founder
jeff@arcovo.ai
315-573-4376
Where we answered each part of your RFP
| RFP | Ask | Sheet |
|---|---|---|
| 1 | Willingness to sign SREG's NDA | |
| 3 | Department-by-department audit | |
| 3 | Evaluate against the forward growth scenario | |
| 3 | Rank by ROI and ease of implementation | |
| 3 | Phased roadmap, buy vs. build, category-level recommendations | |
| 3 | Organization and governance model | |
| 4 | All nine functions in scope | |
| 4 | 140-item list as input, with independent interviews | |
| 5 | All six deliverables | |
| 6 | Pricing and approach for Options A, B and C | |
| 7 | How we gather information, and from how many people | |
| 7 | How findings translate into prioritization |
| RFP | Ask | Sheet |
|---|---|---|
| 7 | Avoiding a product in search of a problem | |
| 7 | Centralized vs. decentralized AI adoption | |
| 7 | Data governance and AI usage policy | |
| 8 | Firm overview and practice areas | |
| 8 | Audit and process-improvement experience | |
| 8 | At least two references with named contacts | |
| 8 | Named staffing plan, seniority, senior staff stay engaged | |
| 8 | Data security and confidentiality practices | |
| 9 | AI depth: findings turned into implemented tools | |
| 9 | Transparent pricing | |
| 10 | Timeline to vendor selection and kickoff |