Mission
Bring data and AI into operations, practically.
Help businesses and schools apply data and AI to everyday work, with measurable impact, the ability to run it themselves after handover, and no dependence on a single vendor.
Digital transformation · Data · AI · Education
Turn data and AI into operating results you can measure.
MindKite Labs works alongside businesses and schools in Vietnam and Southeast Asia to standardize processes, build a solid data foundation and bring AI into everyday work, with clear KPIs at every stage.
- Every department reports different numbers, and weekly meetings spend half the time agreeing on them.
- Expense, order and leave approvals are scattered across chat groups.
- End-of-day reports are compiled by hand from Excel, POS and e-commerce platforms.
- You have tried AI tools but are unsure where they fit or how to measure the impact.
About us
Helping businesses and schools take off with data and AI.
MindKite Labs advises on and builds digital transformation, data and applied AI solutions for small and mid-sized businesses and education organizations in Vietnam and Southeast Asia. We work directly with the people who run operations, start from real problems and measure results in numbers.
What our name means
- MindMindset
- Every change starts with how people think and work. Technology only creates value when it serves the right thinking and the right people.
- KiteThe kite
- A kite rises with the wind and a string that holds it steady. Data and AI are the wind; clear processes are the string. Without the string, the kite cannot fly.
- LabsThe lab
- Start small, measure, then scale. Every solution is proven on real data before it is rolled out across the organization.
Vision
Every important decision is backed by data.
To be the trusted digital transformation partner for small and mid-sized businesses and education organizations in Vietnam and Southeast Asia, where people are freed from repetitive work to focus on creating value.
Services
Five capabilities, one goal: an organization that runs faster and more accurately.
01
Digital transformation
Build a roadmap based on real readiness, choose tools that fit the budget and make the most of existing systems.
Example: move expense approvals out of chat groups into one approval flow with history and deadlines.
- Digital maturity assessment
- Phased 6–18 month roadmap
- Digitized forms, approvals and records
- Vendor-neutral software selection
02
Data & BI
Agree on metric definitions, bring data from many sources into one place and build dashboards leadership actually uses every morning.
Example: end-of-day revenue and inventory reports that update automatically instead of being compiled by hand late into the evening.
- KPI dictionary
- Data warehouse and automated pipelines
- Executive, sales and operations dashboards
- Data quality and access governance
03
Applied AI
Pick the right work for AI, keep a human reviewer and measure the error rate. No AI just for the sake of AI.
Example: an assistant that answers new staff questions on internal policies and procedures, with citations to the source documents.
- AI use case screening and prioritization
- Internal knowledge assistant
- Document extraction and feedback classification
- Demand and inventory forecasting
04
Operating processes
Write the process down before automating it: who does what, when, and how it is measured, so the system does not depend on a few individuals.
Example: standardize the order-to-delivery process and attach a processing-time KPI to each step.
- Current and target process maps
- SOPs and RACI matrices
- Operating KPIs by department
- Automation of repetitive tasks
05
Education transformation
We work with schools, training centers and corporate learning teams to digitize academic operations, make use of learning data and bring AI into teaching with proper oversight.
Example: track attendance and learning results on one dashboard and flag at-risk learners early so teachers can step in.
- Digital admissions, academic records and tuition
- Attendance and learning outcome dashboards
- AI assistants for lesson planning and grading, with teacher review
- Digital and AI skills training for staff
Delivery process
Seven steps, one closed loop. It ends with measurement, not handover.
Each step has concrete deliverables for you to approve before moving on.
Step 01
Ideation — research and define the problem
Interview the people doing the work, observe the real process and review existing data. The goal is to find the true bottleneck, not a wish list.
- Deliverables
- Problem map and opportunities ranked by impact and effort
- Typical duration
- 1–2 weeks
Step 02
Design — target process and solution
Map the target process, data model and interface prototypes. End users review and comment from the first sketch.
- Deliverables
- To-be process maps, data model, tool mockups
- Typical duration
- 1–2 weeks
Step 03
Validation — agree on scope, cost and KPIs
Leadership and user representatives review the design together. We measure a baseline so results can be compared after rollout.
- Deliverables
- Agreed scope, baseline KPIs, risk assessment, go/no-go decision
- Typical duration
- 3–5 working days
Step 04
Development — build in short cycles
Work in two-week cycles with a demo on real data at the end of each. Changes are logged and reprioritized openly.
- Deliverables
- Dashboards, automation flows, AI models, updated SOPs
- Typical duration
- 2–8 weeks
Step 05
Testing — run in parallel with the old way
Reconcile numbers between the new system and the current way of working, and check permissions and edge cases before switching over.
- Deliverables
- UAT sign-off and resolved issue log
- Typical duration
- 1–2 weeks
Step 06
Deployment — roll out team by team
Role-based training, a gradual department-by-department switch and close support in the first week. Every system has an internal owner.
- Deliverables
- Live system, user guides, trained internal owners
- Typical duration
- 1–2 weeks
Step 07
Re-evaluation — measure results, start the next loop
After 30, 60 and 90 days, KPIs are measured again against the baseline. New issues become input for the Ideation step of the next improvement loop.
- Deliverables
- Impact report against baseline, improvement backlog for the next loop
- Checkpoints
- 30 / 60 / 90 days — back to step 01
Step 07 loops back to step 01: digital transformation is continuous improvement, not a one-off project.
How we work together
Start small. Scale once you see results.
Starter
Quick assessment
2 weeks
Assess current processes and data, and identify three opportunities to tackle first, with effort estimates.
Most common
Scoped project
2–4 months
All seven steps for one specific problem, with re-evaluation after 30, 60 and 90 days of operation.
Long term
Monthly partnership
From 3 months
We act as your outsourced data and operations team and reprioritize the work every month.
Pricing is quoted per scope after our first conversation.
FAQ
Questions organizations often ask before getting started.
Does a small business need AI right away?
Usually not yet. Clean data and written-down processes pay off sooner. AI delivers once those two foundations are in place.
Do we have to buy new software?
No. We make the most of the tools you already use, such as Google Workspace, Microsoft 365, Excel or your accounting software, and only recommend new tools when there is a clear reason.
How is our data kept secure?
We sign a confidentiality agreement before accessing any data, grant only the minimum access needed, never use client data to train external models, and comply with applicable personal data protection laws.
Who runs the system after handover?
Each system has a trained internal owner and user documentation. You can choose the monthly partnership if you want continued support.
Contact
A 30-minute conversation about your challenge.
Tell us briefly about your organization and what you want to improve. We reply within one working day.
Email us
support@mindkitelabs.com