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Three weeks of discovery. What would've taken eight.

Step Up Tutoring · Discovery → Prototype → Launch plan · Compressed with AI

Built on our Spectra philosophy — one shared source of truth, every stakeholder’s perspective.

How it came together

A referral from inside the board.

Ankita Kaul — Vice Chair of Step Up’s Board of Directors, and Director of Innovation & Technology at Stanford’s HEARTS Lab — introduced us. She’d seen our work through a Stanford engagement and knew the Step Up team needed partners who could move fast without breaking what was already running. She watched the discovery unfold alongside the team.

Btw — had the SUT team seen the vibe-coded dashboard previously at all? I’m sure folks that haven’t seen it before may have their mind blown.
Ankita KaulVice Chair, Step Up Tutoring Board of DirectorsDirector of Innovation & Technology, Stanford HEARTS Lab

The client

Step Up Tutoring

Step Up Tutoring is a nonprofit serving tutors, students, and families across Los Angeles. Over the years, their operations had accumulated a patchwork of tools — an operational database holding matches and session history, a workflow-automation layer stitching those tables into daily rhythms, and roughly a dozen integrated systems feeding in from every direction. Every new feature cost more than the last, every audit question took weeks. Operations could not stop while any of this was examined. The board wanted a clear answer: rebuild, or keep patching? They brought us in to find out — fast, and without anything breaking underneath. The shape repeats across sectors: the same play runs for healthcare systems, regional banks, manufacturers, and civic agencies — different stacks, same board waiting for an answer, same rule that operations cannot stop.

Our process

Five steps, three weeks.

Same five moves we would have made in seven or eight weeks without AI. Agents did the audit, the mapping, the option-modelling, and the plan-drafting — our team did the stakeholder conversations, the judgment calls, and the board-facing framing.

  1. 01

    Listen.

    We sat with every stakeholder group — tutors, families, operations, the board — and mapped what was working, what wasn’t, and where the real constraints lived. The biggest one: operations cannot stop. Any change had to be provable before it was committed.

    AI · AI transcribed every interview, clustered every concern, and surfaced the patterns a human reviewer would have taken a week to see.

    transcription-agent
    speaker-labeled transcripts from every call
    theme-clustering-agent
    grouped hours of conversation into patterns that mattered
    constraint-extraction-agent
    surfaced the hard lines the build could not cross
  2. 02

    Audit.

    We pointed agents at the operational database, the workflow-automation tool, and the twelve integrated systems around them. Every table, every automation, every dependency — inventoried, classified, and read against what the stakeholders had told us mattered.

    AI · Agents cataloguing in parallel compressed a multi-week stack audit into days. Our team reviewed the findings and decided which ones changed the plan.

    schema-cataloguing-agent
    every table, every field, every relationship
    automation-mapping-agent
    traced every workflow to the tables it read and wrote
    dependency-graph-agent
    mapped the twelve integrated systems and how they touched
  3. 03

    Shape.

    We modelled three migration paths — keep-and-patch, partial rebuild, full rebuild — against the audit findings and the stakeholder needs. Each path came with a downtime profile, an operational-risk profile, and a phased sequence the board could actually sign off on.

    AI · AI drafted the option comparisons, the migration sequencing, and the risk register. Our team edited, pressure-tested, and picked the defensible recommendation.

    option-modelling-agent
    keep-and-patch, partial rebuild, full rebuild — side by side
    sequencing-agent
    phased each path with a downtime profile
    risk-register-agent
    risk matrix read against every audit finding
  4. 04

    Prototype.

    We stood up a clickable dashboard of the future admin experience in a week — matches, health scores, session tracking, board reporting — so every stakeholder could see the rebuild before committing to it. Nothing production, nothing touching live data. A prototype the team could click through and argue with.

    AI · AI stood the prototype up in days instead of weeks. That single artifact turned the rebuild-vs-patch conversation from abstract to concrete — the moment the team saw it, the decision became easier.

    ui-scaffolding-agent
    stood up the clickable shell across four screens
    screen-design-agent
    polished each surface against the stakeholder it was built for
    mock-data-agent
    synthetic matches and sessions — no live data touched
  5. 05

    Plan for launch.

    We handed over a launch plan designed around the one non-negotiable: operations cannot stop. Phased cutover, parallel-running windows, rollback gates, and a day-by-day downtime budget. Plus a full handover packet of audit findings, migration options, and decision records.

    AI sequenced the cutover, modelled the downtime budget day by day, and assembled the handover packet — so the team walked into the board meeting with every trade-off already written down.

    cutover-sequencing-agent
    phased rollout, parallel-running windows, rollback gates
    downtime-budget-agent
    day-by-day acceptable-downtime ledger
    handover-packet-agent
    audit, options, and decision records in one packet

What comes next

Build phase — agents and humans, side by side.

Discovery produced the map and the plan. The build phase runs the same way — AI agents doing the work that scales, our engineers making the calls that don’t.

What agents will do

  • Stand up the new admin platform module by module, test-first.
  • Run the migration against a shadow copy before the live cutover, every day.
  • Keep the decision record current — every trade-off written down as it happens.
  • Flag drift between the plan and the build the moment it shows up.

What the team will do

  • Own the stakeholder conversations — families, tutors, operations, board.
  • Sign off on each migration gate before the next module goes live.
  • Make the judgment calls AI shouldn’t — scope changes, exceptions, timing.
  • Keep operations running the whole time. That is the measure.
ops table → normalizedzoom/apr-14 · transcript intutor concern logged12 integrations auditedrebuild path picked ✓downtime risk flaggedmatch health → tutorsboard: “when do we start?”

Every source the team already uses — the operational database, the workflow-automation tool, Gmail, Zoom, Slack, Figma — feeds one shared record. Agents read from it and write back to it. Every stakeholder sees the surface tuned to them.

What we handed over

A prototype the team could click through.

Four screens that made the rebuild argument tangible. One shown in full below, three summarized beside it. Not a shipped platform — a clickable preview that turned the board conversation from “maybe” to “when.”

Step Up admin dashboard prototype — Matches module. A list of students paired with tutors, each row showing match status, health score, session count, and next meeting time.

Tutor-matching surface

Matches dashboard — prototype

The daily view — prototyped in days with AI. Active tutor-family matches with a single health score per row. Operations could see what they’d have — green, yellow, orange — without a single line of production code written.

Scope & budget surface

The board’s view. Engagement scope, phased rollout, and the downtime budget — prototyped so the decision-makers could argue with it.

Session-tracking surface

Operations’ view. Per-session logs, tutor notes, engagement signals — what the live system would feel like once built.

Board dashboard

Every decision, every phase, every module — surfaced for the stakeholders who sign the check.

Outcomes

What the team walked out of discovery with.

  • A full audit of the operational database, the workflow-automation layer, and the twelve integrated systems — read against real stakeholder needs, not assumptions.
  • Three migration paths modelled side by side, each with its downtime profile and operational-risk profile — so the board could pick with eyes open.
  • A clickable prototype of the future admin experience — enough for operations, tutors, and the board to see the rebuild before committing to it.
  • A launch plan designed around the one rule we could not break: operations cannot stop.

Want to go deeper?

Every interview, every audit finding, every migration option, every line of the launch plan is queryable. Ask the Step Up engagement anything — answers are cited from the actual project documents, sanitized of any confidential detail.

What this looks like for you

A first engagement, sized to your stack.

The playbook compresses the same way whether you are a five-thousand-person health system, a regional bank, a state agency, or a fifty-person operations team. A week of listening, a week of auditing, a week of shaping the answer. Here is what the first three weeks would look like if we started next Monday.

  1. Week 1

    Listen and frame.

    We sit with the three or four stakeholder voices who matter most — whoever is closest to the problem, whoever signs the decision, whoever operates the thing day to day. You get back a one-page brief that names the real constraint, not the easy one.

  2. Week 2

    Audit the stack.

    Our agents catalogue every table, every automation, every integration that touches the area in scope. You get a readable map — one document — of what you actually have, versus what you think you have. Your InfoSec lead gets the vendor-risk packet that same week.

  3. Week 3

    Shape the options.

    Three paths modelled side by side, each with a cost profile, a timeline profile, and a risk profile. You walk into the next board meeting with a defensible recommendation already on paper and a clickable prototype people can argue with.

Start a 30-min scoping call

Prefer to kick the tires first? Forward your three biggest unknowns to mayuresh@betacraft.io and we’ll come to the first call already prepared.

Partial list — drawn from 50+ client relationships

Teams and organizations we have built for

We have built platforms, AI tooling, and full products for partners across education, philanthropy, research, healthcare, fintech, civic tech, and aerospace. The list below is a partial cross-section — some engagements are under NDA, some are pre-launch — and every logo here is work we can walk through on a Zoom.

  • iSoftpull
  • GreenFig
  • Teplo
  • CodePath
  • Programination
  • Gates Foundation
  • Stanford University
  • Ziplines
  • Skyryse
  • Georgetown University
  • Ashoka Changemakers
  • Intel
  • iSoftpull
  • GreenFig
  • Teplo
  • CodePath
  • Programination
  • Gates Foundation
  • Stanford University
  • Ziplines
  • Skyryse
  • Georgetown University
  • Ashoka Changemakers
  • Intel
25M+End users reached10+Industries covered95%On-time delivery
The 60-second version

Who is BetaCraft

BetaCraft is an AI-native product engineering firm — agents ship code alongside humans on every engagement. Led by founder Ratnadeep Deshmane and partner Mayuresh Soni — both serial founders who built, scaled, and exited digital products before joining forces at BetaCraft. We run digital transformation for mission-driven institutions across education, tutoring, philanthropy, research, and healthcare.

Education is not new territory. Step Up Tutoring — the engagement on this page — came to us through Ankita Kaul, Vice Chair of Step Up’s Board of Directors and Director of Innovation & Technology at Stanford’s HEARTS Lab. Our active Georgetown University partnership ships credential-to-jobs data visualization across fifty-five U.S. metros for the Center on Education and the Workforce. Our long-running Stanford Solutions Science Lab partnership (Our Voice, CORD) is delivered by a remote eight-engineer squad working in daily partnership with the California-based faculty team. For Step Up, the points of contact are named and accountable: Mayuresh Soni as engagement lead, Chetan Phatak as tech lead.

Our engineers slot directly into your delivery process — discovery calls, stakeholder interviews, approval gates, security and vendor-risk review — and rewire it from the inside. Six-week discoveries compress to two. Quarterly release trains compress to weekly. Your internal team gets faster without getting bigger.

That is how the Step Up discovery wrapped in weeks, not months. Every person on the project team moves the work forward directly, not just the engineers. The executive director asks a question in plain English and gets a sourced answer. The operations lead files a concern and it lands as a tracked risk. Engineers prototype; everyone else stops waiting on a ticket and starts shaping the build too.

Enterprise buyers ask how we get through their vendor-risk and InfoSec review — so we answer that upfront. Every engagement ships with phased sign-off gates at the module level, a rollback path executable inside a single business day, vendor-risk packets ready for the questionnaires clients actually send, and SLAs written to match the client’s procurement standards. The compliance experience listed below is the public face of that same discipline.

We work through a philosophy we call Spectra: one shared source of truth per project, refracted so every stakeholder — from the board to the operations team to the tutors and families — sees what matters to them, in their voice.

Clients served
50+
Projects delivered
150+
Shipping since
2019

Compliance experience

We are not a certified entity — we build products that pass our clients’ audits. BetaCraft engineers have shipped into these regulatory regimes end-to-end: requirements mapping, control implementation, audit support, remediation.

  • FERPA — built for

    Education platforms handling student records under client FERPA review.

  • SOC 2 Type II — built for

    DevSecOps stack wired into client certifications.

  • HIPAA — built for

    Telehealth and medical-imaging products — passed client HIPAA audits.

  • Nonprofit-sector fit

    Board-ready reporting, phased rollout planning, audit-trail documentation — built into every engagement.

A case study from BetaCraft · Running on Spectra.

Spectra platform