The AI operating layer proven on a real P&L.
Built inside a real operating company.
Maxify AI is the operating system that transforms established enterprises into AI-native companies — turning fragmented systems, manual workflows and institutional knowledge into an AI-native operating model.
Maxify’s mission is to make world-class AI operating capability accessible to every company. Every company deserves to run like the best-run company.
Enable ordinary people to achieve extraordinary results.
One goal: your margin.
I channelled every pain point of running a real multi-country, multi-channel company into this AI operating system.
Past a certain size, your company runs on you.
- Too many meetings but no follow-ups.
- Everyone does it their own way.
- Different teams fight.
- Key-person risk.
- What's the ground truth?
- What's everyone actually doing?
- Why is my margin dropping?
The fastest credible path to an AI-operated company.
One outcome. Your existing data. Governed agents live in 30 days — the foundation, not a pilot you discard.
No trial and error
You don’t lack AI tools. You lack the end-state architecture.
A result in 30 days
One workflow, in production — not a slide.
Nothing destabilised
Sits above your stack. Incremental, reversible. No ERP replacement.
Capability, not dependency
You keep the data, the decisions, the knowledge.
Your whole company on one governed console — AI operators do the work. No black boxes.
The AI operating layer that runs toward your margin.
Agents built for how an enterprise actually runs — every function covered, stronger together.
Proven inside Sunnystep — each function with AI agents owning real workflows and a live scorecard for the outcome.
Executive Mission Control
Company-wide KPIs, decisions & accountability in one place.
Finance
Reconciliation, AP, cash-flow & variance alerts.
Marketing & Growth
Campaigns, creative, paid-ads & SEO.
E-commerce
Listings, pricing, promotions & cart recovery.
Marketplace & Channels
Listings, inventory & pricing synced across marketplaces.
Merchandising
Demand forecasting, assortment & markdowns.
Supply Chain
Replenishment, supplier POs & stock-risk alerts.
Product
Quality gates, range discipline & roadmap.
Operations
SOP execution, exception handling & daily reporting.
Customer Support
Ticket triage & on-brand replies across channels.
CRM & Retention
Win-back, loyalty & churn-save flows.
HR
Screening, offers, onboarding & coverage gaps.
Business Development
New retail doors, channels & markets, wholesale & partnerships.
Real workdays. A human on every approval. Across all business functions.
Deliverable: DBS-SGD (2026) · rows A3188:L3208
Verified: ledger ties to the DBS bank feed; exceptions flagged, none blocking.
Remaining: none.
An afternoon of finance work — one sentence. Reconciled to the exact rows, checked before it says done.
2026-07-31 · CP1 Pte Ltd · Chinatown Point_GTO_Jun26 · DR 131.30
Status: applied · rows inserted 1 · row 3244 · recurring rent/utility applied.
Invoices post themselves — after one human tap. The money stays human.
A stock check became a merchandising call — one thread. Every number traced to source. No analyst, no lag.
Customer: spiceng · Platform: Shopee · Order 260715PRE28YFV
On duty: @Amy @Shamini
📥 Reserve: Balance Penny Loafer Mules · Oat · 39
📤 Returning: Dream Lace-up Mules · White · 40
Online store and shop floor, finally in sync. The exchange is staged before the customer walks in.
Planned incoming: 79 pairs · New SKCs: 3 · Restock SKCs: 23
Return-to-WH included prepare 2 return SKCs (~18 pairs) before the incoming arrives.
Stock lands to a store that's already prepped. The floor is ready before the truck arrives — no scramble.
Two product edits, engaged-first → broad. Both Klaviyo drafts, ready to review & send — built to A/B test angle vs audience.
- E1 · The Oxford Edit — "The Oxford your feet won't dread 👞" · Engaged 90d + Repeat
Open the Oxford Edit → - E2 · The Walker Edit — "Wide feet? Flat feet? Meet your Walkers 🚶" · Win-back + max reach
Open the Walker Edit →
Two on-brand A/B emails — zero designers. Written in your voice, split by audience, ready to send.
Your busiest channel, answered in seconds. On-brand, confidence-scored, held until a human hits Send.
- Break down 2026 complaints by product × cause — Felishia · 8 Jun
- Unify CS + store after-sales SOP — Felishia, Gail · 11 Jun
- Connect OTB replenishment to the gateway — Yutong · 19 Jun
Every meeting becomes owned actions — chased to done. The say-do gap closes itself.
Guardrail: AI drafts & diagnoses; every render / spend needs human approval.
Every agent curates its own brain — sharper daily. Drop a link; it captures, verifies, turns it into a plan.
Posting today; only got the Balance Runner, will feature it with code CHEVON5OFF + tag @sunnystep.official.
- Shopee program — draft declines, keeps the collab on Sunnystep
- Usage rights — draft proposes a limited paid-usage option
Your whole influencer program, run end to end. Every reply drafted; only the business calls reach you.
Key metric — confirmed technical-AI interviews 18 vs target 10 · invitation-to-confirmation 56%.
- New applications 32 · P0 candidates 7
- Interview invitations 32 · interviews confirmed 18
The whole hiring funnel, reported weekly — automatically. Sourcing to confirmation, no one chasing numbers.
Added to coach memory as durable behaviour · created a reusable Skill proposal.
Nothing slips — and it gets smarter when praised. A vague task became owned, proven, then a reusable skill.
Owners tagged below — action your items by the due date or reply done.
☐ Confirm 5% cashback in points issues and redeems at the till and online — due Sat 26 Sep · overdue · Quynh
Note: still the blocker. Mechanic changed 28 Sep. Store credit was dropped because it could not be confirmed across both systems; points has to clear the same bar now the offer runs in-store and online.
☐ Counter card + staff script — due Thu 8 Oct · Aliya
☐ Retail briefed, Mon–Thu only — due Fri 16 Oct · Gail
A campaign becomes owned, dated actions — and the blocker is named. The agent does not just report that something is late; it says what it blocks and who has to decide.
Unreserved alternatives: thermos 132 · massage gun 169 · travel pillow 67.
Proposed: a different gift per buy tier, so the two campaigns stop competing for one pool.
Otherwise Roam launches with no gift.
Two campaigns, one pool of gift stock — caught before either launched. The agent read both plans against live inventory, found the collision and put every unreserved alternative on the table. A person made the call.
Not just operators — a team that thinks with you. Your AI C-suite debates strategy and sharpens the call.
We proved it on a real P&L, in a real operating company.
Maxify was deployed inside Sunnystep — an independent, science-led retail company. Same business, higher margin, a fraction of the team — with AI agents absorbing the manual and coordination load.
6 months, phased, end to end — proof over promises.
| Function | Before | After |
|---|---|---|
| Managers | 7 | 0 |
| Marketing | 8 | 2 |
| E-commerce | 3 | 1 |
| Merchandising | 2 | 0 |
| Product & supply chain | 6 | 2 |
| Retail operations | 5 | 2 |
| HR | 2 | 1 |
| Finance | 2 | 1 |
| Customer support | 2 | 1 |
| Total | 37 | 10 |
From first workflow to an AI-operated company.
Align → Launch → Prove → Scale → Orchestrate → AI-operated. Two tracks run the whole way: business value, and the governance that keeps it controlled.
Align & redesign
Name the number the process exists to move, measure the baseline, and rebuild the process to move it.
An owner who can approve a changed process — not just describe the current one
Launch
Put the first governed agents into daily work, through the chat tools your team already uses.
Human gates and audit trail
Prove
Verify value, safety and adoption — run in shadow beside the people doing the job today, with no live authority until it beats the baseline.
Mission Control and fallback
Scale
Replicate proven patterns internally, function by function.
Internal team extends the system
Orchestrate
Coordinate agents across functions, not just inside one.
CEO Dashboard and exceptions
AI-operated
Operate toward company objectives.
Controlled autonomy and optimisation
Ten people. Twenty-two agents. One company.
Sunnystep today. Every function has a named human who owns the outcome; the agents underneath do the execution and write the results back. 37 people to 10 — not by asking anyone to do more, but by giving each of them a team.
The human sets intent and approves; the agent executes and reports back. Each agent has a written mandate, a Lark identity, a scheduled loop and an auditable run log. Every agent owns a number and is measured against it weekly — and a named person makes the call on anything that reaches a customer, moves money, or changes someone’s job.
Grow output and margin — not headcount.
Company-wide AI transformation — immediate P&L impact.
AI Product Modules
The system that runs the work.
Seven productised modules: Governed Access · Process Engineer · Company Brain · Agent Fleet · Mission Control · Agent Studio · Domain Expertise Marketplace.
Change Management
Adoption is the product.
Strategy · Prepare · Discover · People — the operating-model and human transformation.
Deployment Team
Embedded until it runs.
A senior 3-person team who've run a real company — working onsite with you, not billed by the hour.
Before we redesign anything, we map the whole company.
Not an org chart and not a flowchart. A living, queryable model of how the company actually works today — built by agents, across every function at once, in weeks rather than a consulting quarter.
Operating Graph = Functions + Processes + Tasks + Roles + People + Skills + Tools + Vendors + Sources of truth + Agents + every edge between them
Not the SOP — the path work actually takes.
The unit of work, timed and costed.
What the job does, not what the title says.
Who holds which skill today.
What the company knows how to do.
Every system, and what it is really used for.
Who is paid for which step.
The source of truth behind each entity.
What already runs without a human.
Every handoff, dependency and single point of failure.
The map is not a report. It becomes the Company Brain the agents read before every action — so it stays true as the company changes, instead of ageing in a slide deck.
We redesign the process before anything automates it.
Automate a broken process and you get a faster broken process. We start from the number the process exists to move — then rebuild the process to move it.
Eliminate
Should this step exist at all? Most of the gain is deletion.
Simplify
Most cycle time is queueing, not working.
Standardise
One way across every entity.
Automate
Only now — on the redesigned process, not the inherited one.
Three artefacts in week one: how it actually runs · where it diverges from your SOP and what that costs · the redesigned process, ready to run.
01Product modules
The system that runs the work.
01Governed Access
Plug in. Don’t rip out.
Governed read and write into the systems you already run — no migration, no data-warehouse project first.
Live on the systems Sunnystep already ran.
02Process Engineer
Redesign before you automate.
Maps the company as a living graph — processes, tasks, roles, skills, tools, vendors, agents and every edge — then redesigns the work before anything automates it. Eliminate, simplify, standardise, automate.
Every function in parallel, in weeks.
03Company Brain
Learned once. Kept forever. Used by every agent.
Your SOPs, workflows, data, skills and know-how in one machine-readable model — what every agent reads before it acts, and what the redesign writes into.
One definition of every entity the company runs on.
04Agent Fleet
Agents that own the workflow, not the task.
Role-based agents, each owning a whole workflow end to end, fitted to your redesigned process and your approval chain, under a named human owner.
22 agent managers across 13 functions, in production.
05Mission Control
See everything. Approve anything. Undo any of it.
The CEO’s live view of the company: every function’s numbers, decisions, owners and exceptions in one console — and where every agent action is measured, approved, versioned and rolled back.
2,298 runs in 30 days — every one logged and reversible.
06Agent Studio
Your team builds. The eval decides.
Your team changes the machinery itself — Brain, Standard and Agent builders, every change evaluated before it goes live.
Builders gated by one eval.
07Domain Expertise Marketplace
Hire agents that have already done the job.
World-class domain-expert agents and skills. A finance agent that has closed a real month; a merchandiser that has killed real stock.
263 shared skills — taught once, inherited fleet-wide.
02Change management
Adoption is the product.
Most AI transformations fail on adoption, not technology.
Maxify Strategy
Target operating model, role-to-agent map & cost-out plan.
Maxify Prepare
Leadership alignment, AI literacy & role transitions.
Maxify Discover
A paid 2–4 week diagnostic → a deployable blueprint. No lock-in.
Maxify People
Train & certify your internal team to own it.
03Deployment team
Embedded until it runs.
A team that’s run a real company — building yours.
AI Strategy Lead
Prioritises where AI pays off first; owns KPIs and ROI.
AI Product Solutions Lead
Turns your real SOPs into agent-ready workflows.
AI Engineer Lead
Builds it on your stack — governance, security, evals, rollback.
With leadership: set goals, mandate, KPIs — and clear blockers.
With operators: capture how it really runs, win adoption.
Routine handled by AI operators — people work at their maximum.
One complete operating system — from principle to P&L.
A safe rollout — nothing goes live until it’s proven.
Pilot in shadow
Run beside the people who do the job today — no live authority yet.
Evaluate
Measure against the agreed baseline. The verdict: proven, fixed, or killed — never "looks good."
Deploy, gated
Promote only what passed to live — with gated authority.
Operate live
Runs governed — measured weekly, reversible any time.
Learn & compound
Verified outcomes write their lesson back — sharpening the next agent.
3 ways to get started.
Start where the risk is lowest and expand to where the value is biggest — only the number of functions changes.
Value Pilot
Value Maximizer
Value Engine
Only the number of functions changes between packages — commercials are scoped to value and company size, shared separately.