Operations softwareNew Haven, CTbuiltbytaymo.com

The operations software that never makes the IT roadmap. I build it in weeks.

I spent the last year as the operator on the other side of this problem, running strategy and operations at a venture-backed company, then building the seven internal systems it now runs on. Requirements intake in week one. Something your team is actually using by week three.

7
Internal systems shipped and in daily use
3wks
Intake to working beta on the CRM build
2
SaaS platforms retired and replaced outright
$7.02B
AUM modeled in the advisory intelligence build

Deployed solutions

Seven systems, all running in production. Select any line for the problem it was built against, what was deployed, and how it is measured.

  • Interface reconstruction · synthetic data · SYS·01
    AccountsLicensesRenewalsInvoicesRecordQuotesOutbound

    Platform license, 240 seats

    ACC-2214Provisioning
    Qualified
    Quote sent
    PO received
    Provisioning
    Invoiced
    Account
    Account ownerJ. Whitfield, Operations
    Billed toNorthfield Group (parent)
    Seats240 · account level
    Renewal01 Apr 2027
    Linked, not copied

    3 hotspots · click one for the decision behind that part of the build

    The problem

    Customer information lived in three places at once: individual email inboxes, a Zoho instance nobody trusted, and an Excel file the Head of Customers maintained herself. The slowest lookup in the company was what did we last tell this customer, and can they see their data yet.

    Account structure made it worse. Academic projects are referenced by the principal investigator but the university pays the invoice. Some pharma customers require their own vendor systems. No off-the-shelf pipeline model fits all three.

    What was deployed

    An internal CRM covering contract research engagements, kit sales, hardware install base and consumables, built on Postgres with quoting, invoicing and automated post-invoice reminders.

    The design constraint drove everything. The intake session produced one finding: she would revert to her spreadsheet the moment data entry got heavy. So the build prioritizes linking over duplication. Lab notes link to the project. The customer data folder links to the project. Generated emails attach to the project. Sample status is tracked at engagement level, not sample level, because engagement level is what the business decides on and sample level is what makes people quit.

  • Interface reconstruction · synthetic data · SYS·02
    Practice intelligenceAdvisor operations consoleViewing asAdminExecutiveLegalResearchAdvisorDemo data
    Executive summaryMonday check-inFriday wrap-upManagement decisions38Legal queue78Research queue88PatternsPipelineP&LBook compositionInsightsCompliance

    The firm is running a 31.1% operating margin on $36.62M of year-to-date revenue. The pressure is not financial. It is concentrated in capacity and client retention: 5 of 60 advisors report no room to take on another household, 77 relationships worth $8.30M have been flagged at risk by the people who own them, and 77 queue items have stopped moving entirely.

    Capacity and delivery

    57 of 60 advisors filed a check-in. 74% of the week's commitments closed by Friday, down from 85%. 14 say they have room and then carry work forward, which is the more useful signal for deciding where a new relationship should go.

    Client base and retention

    77 relationships carrying $8.30M of annual revenue have been named at risk more than once by the advisor who owns them. Efficiency across the group is wide: the strongest book returns $1,807 per client-facing hour against $75 at the other end.

    Operations and escalation

    38 decisions sit with management, 7 marked high urgency, the oldest open 43 days. 77 items have not moved in 14 days or more, which is the number that decides whether people keep filing check-ins at all.

    Succession and concentration

    21 advisors with seventeen or more years at the firm hold 41% of assets. That is the succession question in one number, and it is distributed unevenly across the four offices.

    Actionable insights10cards, each pairing an observation with a recommendation somebody can be assigned
    AshfieldHealthy
    29 advisors · 220 relationships
    Revenue$26.95M
    Per advisor$929K
    Contribution margin29%
    Reporting no room26%
    Commitments delivered79%
    Revenue at risk10%
    Held by 17+ yr advisors48%
    Watch: succession exposure runs above the firm norm.
    NorthgateWatch
    12 advisors · 93 relationships
    Revenue$13.74M
    Per advisor$1.15M
    Contribution margin33%
    Reporting no room13%
    Commitments delivered80%
    Revenue at risk23%
    Held by 17+ yr advisors46%
    Watch: retention risk well above the firm norm, succession exposure above it too.
    RowleyHealthy
    11 advisors · 84 relationships
    Revenue$12.63M
    Per advisor$1.15M
    Contribution margin35%
    Reporting no room22%
    Commitments delivered79%
    Revenue at risk9%
    Held by 17+ yr advisors16%
    Nothing pressing. Margin, capacity and retention all sit within range.
    SeldenHealthy
    8 advisors · 68 relationships
    Revenue$7.95M
    Per advisor$994K
    Contribution margin31%
    Reporting no room13%
    Commitments delivered77%
    Revenue at risk16%
    Held by 17+ yr advisors49%
    Watch: succession exposure runs above the firm norm.
    Generated · synthesises the Monday and Friday check-ins, the CRM, the ledger, payroll and advisor calendars

    4 hotspots · click one for the decision behind that part of the build

    The problem

    A wealth management firm running on a CRM and an AI note-taker that between them produced a great deal of data and very little decision support. Leadership could see activity. They could not see which advisor had capacity next month, which client relationships were quietly at risk, or where succession exposure was concentrating.

    What was deployed

    A role-gated intelligence dashboard across five permission levels, with capacity-to-pipeline matching, an at-risk client watchlist, a stalled-item detector and succession exposure by advisor tenure.

    The check-in instrument was built to defeat reporting theater. Nobody self-rates bandwidth, confidence or performance, because those numbers are social rather than real. Monday asks for three deliverables, one capacity question, and what management needs to decide. Friday asks what actually happened and what took longer than it should have. Every insight card carries the finding with its number, clickable evidence drilling to the underlying rows, a recommendation specific enough to assign to a named person, and one line stating what would change the conclusion.

  • Interface reconstruction · synthetic data · SYS·03
    All lanesKanbanGanttNeeds attention
    Project queue
    In progress
    Complete
    Lane A
    Vendor security questionnaire
    28 Mar
    Renewal negotiation, logistics
    12 MarNeeds attention
    Q1 board pack
    04 Mar
    Lane B
    Supplier scorecard
    02 Apr
    Onboarding runbook
    21 Mar
    Access review
    25 Mar
    Lane C
    Site survey, north
    19 Mar
    Warranty terms
    27 Mar
    Headcount plan
    28 Feb

    2 hotspots · click one for the decision behind that part of the build

    The problem

    Remote staff spread across time zones, a seat-based tracker the company was paying for, and management still asking for status in Slack because the board did not answer the question they actually had, which was what is blocked and who is blocking it.

    What was deployed

    One shared board with a swimlane per person, toggling between kanban and Gantt. Color coding is tied to urgency rather than to status column, because a card sitting in In Progress for three weeks is the problem and a status column will never say so.

    Needs Attention is a resolvable flag traceable to whoever raised it, not a column, so a blocked item stays visible in its real stage instead of being parked. Card descriptions are a running dated log rather than a single overwritten field. A master aggregate view filters across everyone at once.

  • Interface reconstruction · synthetic data · SYS·04
    71Steady week11 of 12 responded · 3 open blockers · 2 decisions waiting
    22/25Response
    12/20Confidence
    13/20Blockers
    16/20Delivery
    15/15Runway
    HomeMonday check-inFriday wrap-upFlags for managementWeek 13Trend
    Weekly brief

    Delivery held at sixteen of twenty for the third week, but two of the three open blockers are now older than a fortnight and both sit with the same lane, which is worth watching before it reads as a capacity problem. One decision has been waiting since the first week of March. Confidence fell four points against a flat response rate, so the change is in how the week felt rather than in who answered.

    Generated automatically · Monday and Friday, 15:00 · nobody is chased
    Team pulse11 / 12responded this week
    High confidence5
    Open blockers3
    Flags for management13items needing attention
    Open blockers3
    Decisions needed10
    Missed deliverables0
    Pipeline$4.2Mtotal open value
    Open deals18
    Won this quarter4

    3 hotspots · click one for the decision behind that part of the build

    The problem

    The weekly leadership meeting spent its first half building a shared picture of the week instead of deciding anything. The picture was assembled by hand, by someone, every week, from sources that had not changed since the last time it was assembled.

    What was deployed

    An executive dashboard fed by an automated pulse bot that collects structured status on a fixed cadence and surfaces it without anyone chasing it. Leadership arrives at the meeting with the picture already built.

    The value was visibility before headcount growth. A company adding staff without a documentation and reporting layer compounds a problem that gets much more expensive to fix later.

  • The problem

    Research trackers become fiction within a quarter. Status is self-reported, nothing checks it, and the board deck ends up describing work that did not happen the way it says it did.

    Meanwhile the artifacts that prove the work exists, lab notebook entries, raw data, result decks, sit in four systems with no link back to the experiment they belong to.

    What was deployed

    A kanban and Gantt tracker with a swimlane per researcher, and a permission model that enforces evidence at the state transition rather than at review.

    An experiment cannot be proposed without a lab notebook link and a raw data link. An owner cannot move their own card to Ready for Review without attaching the slides. Completed cards record who reviewed them. Only admins can move a card into In Progress or Completed, and every transition after proposal is timestamped.

  • The problem

    Three recurring customer communications, prospect qualification, quality control updates and final deliverable handoff, were being rewritten from scratch each time by whoever happened to be sending them. Tone drifted, detail was inconsistent, and no copy of what was sent lived anywhere the team could find later.

    What was deployed

    A template engine covering all three classes, producing consistent outbound in a fraction of the time.

    It was then folded into the CRM rather than left standing alone, so every generated email attaches to its project. The answer to what did we last tell this customer stopped requiring a search of someone's sent folder.

  • The problem

    Internal tools accumulate faster than governance does. Each one arrives with its own URL, its own login and its own idea of who should be allowed in. Six months later nobody can answer who has access to what, which is the first question any security review asks.

    What was deployed

    A single portal consolidating the internal tools behind Google single sign-on, reverse-proxying each application under one governed domain.

    Access is granted and revoked in one place, tied to the identity provider the company already runs. The shared secret is stored as a sensitive environment variable and rotated on schedule. This is the piece that makes the rest of the stack answerable to an enterprise security questionnaire.

Also delivered / Website buildsStack / Next.js, Postgres, Railway, VercelYou own the repository and the database.

Start

Send me the process you are least happy with.

I will send back a one-page read on whether it is worth building for, at no cost. If it is not worth building, I will say so.

  • 01 / The processWhat it is, and who does it today.
  • 02 / Held together bySpreadsheet, shared inbox, a SaaS tool you are underusing, or all three.
  • 03 / People affectedRoughly how many, and in which function.
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