AI for EdTech

Product engineering for EdTech startups and training providers

Ship the product, then add the AI your buyers ask about.

Datics builds MVPs, portals, marketplaces and payments for EdTech startups and training providers, and adds AI modules when you are ready, from the same team.

Built for: Funded EdTech startups, academies, marketplaces and training providers.

apply.northstarcampus.com / find-a-program

Northstar College · Pathly

Demo
  • I do medical billing and want to move into healthcare IT. I can do two evenings a week and need to start before spring. What fits?

Step 1 of 5

Illustrative demo on a fictional institution. Not client work.

Where these products get stuck

  1. 01

    The roadmap is bigger than the team

    Investors and first customers expect a working product and an AI story, and the same few engineers own both.

  2. 02

    Most of it is not new

    Profiles, search, booking, payments and admin portals are the same every time, and building them from scratch burns runway.

  3. 03

    AI bolted on late

    An AI feature added after launch, without evals or cost limits, becomes the support ticket nobody can close.

AI inside your product

The modules that fit this kind of platform.

Each one is a reference build shown on a fictional institution. It runs inside your product, on your data, and ships under your name.

Pathly

AI course and program recommendations

An advising agent that knows your catalog and books the next step.

Fits: Admissions, enrollment, CE and corporate learning catalogs

Rehearsly

AI skills practice and roleplay

Voice roleplay practice with rubric scoring, inside your course.

Fits: Workforce learning, CE, health-professions education, bootcamps

MVPs, portals and payments

MVP and V1 builds for EdTech startups, learner and provider portals, marketplaces, booking and tuition payments by card and ACH for training providers.

Built on marketplaces and payment portals we have delivered.

How it works

One AI feature, working inside your product, in two weeks. $10,000, fixed.

Startups usually start with a fixed-scope build for the product, or with the Sprint when the product exists and the question is which AI feature to ship first.

  1. 01

    EdTech Product Review

    30 minutes, free

    We look at your product with you and pick the module or capability that protects your next release, what it would cost to serve, and what your customers' security review will ask.

  2. 02

    The Sprint

    $10,000, two weeks, fixed

    One AI feature working inside your product: running in your staging environment on your catalog, documents or synthetic data, behind a feature flag, delivered as pull requests. You also get quality and safety evals, a cost estimate on two models, a data-flow sheet and a fixed-price quote for production.

  3. 03

    Targeted Unlock, then Capability Waves

    Quoted at the end of the Sprint

    The first production capability, delivered by pull request into your repo with no standing production access. Then the next module, on the foundation the first one built.

Built for education data

Controls your customers' security reviews ask about.

Each control is a design fact about how the module is built and how we work, not a compliance claim.

  • Runs on your catalog, documents or data through the APIs your product already exposes. No rebuild.
  • Sprint work uses synthetic or de-identified data and ships as pull requests to your repo. No production student data.
  • Every answer that matters shows its source; material actions go to a person for approval.
  • Built around FERPA, COPPA, accessibility and institutional requirements.
  • Built to ship under your product's name. Model and hosting are your choice.

We build around your FERPA, COPPA, accessibility, security and institutional requirements. Compliance depends on the complete product, contracts, policies and operating environment; Datics does not present software engineering alone as legal certification.

How we handle student data

Product improvements you can measure

What we agree to measure in the Sprint, so the production decision rests on your numbers, not ours.

01

Faster V1

Measure

Weeks from scope to first paying customer

02

Fewer rebuilds

Measure

Share of the V1 codebase kept at Series A

03

AI with a cost model

Measure

Inference cost per active learner

Proof

What we have built that this rests on.

33 case studies across 17 industries, 19 of them AI products or brownfield AI builds shipped inside software customers already use. Each EdTech module starts from one of those engines, so you are not paying for us to learn.

Learning-agency directory

EdTech · Directory / Marketplace

A vetted, subscription directory that helps education buyers find and compare learning agencies

A members-only directory of vetted education agencies with search, filters, shortlists, moderated comments and Stripe subscriptions, built end to end in six milestones.

EdTechMarketplaceMembership
Read case study

Leadership-development practice app

EdTech · Learning App / Mobile & Desktop

A leadership-development practice app taken from the web to iOS, Android and desktop

A daily leadership practice built on seven inner archetypes, taken from a web app to native iOS, Android, Windows, macOS and Linux apps from one codebase.

EdTechLearning appCross-platform
Read case study

Adaptive Intake Platform

Healthcare SaaS · Adaptive Intake / Multi-Tenant SaaS

Adaptive intake taken from a one-site prototype to a multi-tenant product

Intake that adapts its questions and writes a structured summary, taken from a single-practice prototype to a multi-tenant SaaS with self-serve onboarding, billing and full isolation.

Adaptive intakeMulti-tenant SaaSData isolation
Read case study

Dawa

Financial Services · Investment Operations Software

Adding production AI around a regulated investment platform without replacing its .NET core

Production AI and automation added around a regulated .NET investment platform instead of rebuilding the core.

BrownfieldRegulatedAWS
Read case study

Voice Roleplay Trainer

Insurance Sales Training · Skills Practice / Voice AI

AI voice roleplay that makes skills practice measurable

Agents pick a scenario, a prospect personality and a difficulty, hold a live voice call with an AI prospect, and get a scorecard, transcript and coaching against the firm's own method.

Skills practiceVoice AIWorkforce learning
Read case study

Read next: EdTech startups: ship the product first, then the AI your buyers ask about

See one module on your own product.

Bring one product, workflow or AI initiative. In 30 minutes we pick the module that fits first, what it would cost to serve and what your customers' security review will ask.

Calls run in US Central time. No generic AI presentation: we discuss your product, users and production constraints.