AI agents for higher education and commerce

Do more with the team you already have.

InSync's AI agents take on the repetitive work in your operations, end to end, inside the systems you already use. Your people keep every decision, and you can see exactly what it's worth.

25M+interactions handled by our agents
95%of pilots go on to production
Agents at work right now illustrative
Higher edTransfer Success Agentillustrative
J
Jordan · prospective transfer student

    Agent control roomTodayillustrative
    0conversations resolved
    0staff hours returned
    0handled without hand-off
    ENEnrollment Agent1,284 prospects · 96% resolvedRunning
    TRTransfer Success22 files ready for reviewAwaiting you
    CSCustomer Support Chat3,410 chats · 81% resolvedRunning
    Agents between people and your systemsillustrative
    Transcript mapped, verdict sent to the SIS
    Why now

    AI is moving from answering questions to getting work done.

    The same three forces are reshaping campuses and storefronts alike.

    The pressure 57%

    of service leaders expect contact volumes to keep rising over the next two years.

    Work is outgrowing teams. McKinsey
    The shift 62%

    of organizations already have AI agents at work, and 23% are scaling them.

    Agents are moving from talking to doing. McKinsey
    The payoff 80%

    of common service issues will be resolved by agents by 2029, at about 30% lower cost.

    Teams get time back for what matters. Gartner
    InSync's answer
    Agents that finish the jobContext, action and the record updated.
    Under your controlThresholds, approvals and a full audit trail.
    Value you can proveMeasured against a holdout from week one.
    More from the research
    • 91% of financial aid offices say each application takes more time and resources than five years ago.2
    • 40% of enterprise apps will include task-specific agents by the end of 2026, up from under 5% in 2025.4
    1. McKinsey, Where is customer care in 2024?
    2. NASFAA, 2025 Administrative Burden Survey
    3. McKinsey, The State of AI in 2025
    4. Gartner, Aug 2025
    5. Gartner, Mar 2025
    What InSync does

    Agents that finish the work, not just answer questions.

    1
    Understand

    Each agent pulls the full context from your systems: who this is, what's due, what happened last time.

    2
    Act

    It completes the task end to end: answers, prepares the file, chases the document, reaches out, updates the record.

    3
    Hand off

    When judgment is needed, it routes to the right person with everything they need to decide.

    IS
    Agent consoleToday · illustrative
    All agents live
    EN
    Enrollment Agent1,284 prospect conversations · 96% resolved
    Running
    RD
    Risk Detection38 students flagged · outreach sent to 31
    Running
    TR
    Transfer Success22 files ready for evaluators
    Awaiting you
    PE
    Product Expert3,410 shopper sessions · 412 carts built
    Running
    ES
    Email Support78% resolved automatically · 41 drafts to approve
    Awaiting you
    What changes

    Faster for the people you serve. Lighter for the people who serve them.

    9.5→5.0Faster response

    Median days from first interaction to a request for information.

    ASU Online
    $11Lower cost

    Cost per inquiry, against a $140 industry benchmark.

    12-campus network vs. UPCEA
    94%Fewer hand-offs

    Of interactions resolved without passing to a person.

    Across production agents
    95%Proven value

    Of pilots move into production, measured against a holdout.

    All pilots to date
    The platform

    One governed layer underneath every agent.

    Our agents, agents we build with you, and agents you already run all work through the same services, connectors and controls.

    Where people reach you
    WebEmailSMSInside the LMSStorefrontStaff portalsVoice (coming)
    Agents
    Enroll AIRetain AICommerce AIBuilt with you in Agent StudioYour own agents
    Shared services
    ContextWho this is, liveKnowledgeCited answersIntentWhat they needPatternsWhat's emergingRecommendationWhat fitsRiskWho needs help
    Your systems
    CanvasSlateSISSalesforceZendeskShopifyGorgiasREST · MCP · LTI
    Agents work together

    One agent spots the risk, another pulls the context, another drafts the outreach. One job, done end to end.

    Every action measured

    Lift is tested against a holdout group, so each agent's value is a number, not an anecdote.

    Bring your own agents

    Agents you already run plug into the same connectors, controls and measurement, so everything is governed in one place.

    Custom agents

    Don't see the agent you need? We'll build it with you.

    Every campus and every retailer has work that no off-the-shelf agent covers. We design those agents with your team, for higher education and commerce alike.

    1. Map the workflow

      One working session on how the work runs today and where it stalls.

    2. Build on the platform

      Built in Agent Studio on the same services, connectors and guardrails as our own agents, so it arrives fast.

    3. Prove it, then go live

      Shadow mode first, then live above your thresholds, measured against a holdout.

    Scope a custom agentIf it reads, decides, drafts or escalates, we can build it.
    AS
    Agent StudioNew custom agent · illustrative
    Drafting
    The brief

    Built from
    Connected to
    Guardrail

    Ready for shadow mode
    Governance

    Governed by design, from the first agent.

    Guardrails by design

    You set confidence thresholds and approval steps for every agent. Anything uncertain goes to a person, and every action is logged.

    A clear line on action

    You decide where an agent recommends and where it acts. Consequential decisions stay with your people.

    Personalization with equity

    Help adapts to each person, and we review outcomes across groups with you to catch disparities early.

    SOC 2 Type IIHECVATGDPR-alignedDedicated environment per clientYour data never trains our modelsTrust Center →
    How we start

    Start with one workflow. Expand when it pays off.

    Phase 1Shadow

    Agents draft every reply and file. Your team approves each one.

    Phase 2Co-run

    Agents act above the confidence threshold you set. The rest still comes to you.

    Phase 3Run

    Agents carry the volume, and we report results against agreed service levels.

    Insights

    Notes from the work.

    Launches, short reads from our team and what we're learning with the council.

    LaunchQ3 2026

    Our multi-agent platform is live

    Agents that work together on one governed layer: one spots the need, another pulls the context, another takes the action. What changed, and what it means for teams running more than one agent.

    Read the update →
    Council notesOctober 2026

    What it takes to trust an AI agent

    Trust is earned with evidence, some decisions stay with people, and choice drives adoption. Takeaways from our governance session.

    See the council →
    PostLinkedIn

    LLM model routing in production

    How we route each task to the right model for cost, speed and quality, and what we learned running it at scale.

    Read on LinkedIn ↗
    PerspectivePlatform

    Every platform now ships an agent. None ships the layer below it.

    Why the services agents call matter more than the agents themselves.

    Read →
    PerspectiveCommerce

    Every conversation makes the store smarter

    Turning the questions shoppers ask into better product pages and fuller catalogs.

    Read →
    Before you start

    The questions leaders ask us first.

    Straight answers on risk, results and what it takes.

    Have a question that isn't here?Ask Ivy, or put it to our product team directly.

    Will it work for us?

    Will AI agents replace our people?

    No. Agents take the repetitive volume, like the same tuition question at 11pm or the fifth "where is my order?" of the hour, so your people spend their time on the conversations that need judgment. Consequential actions, such as messaging a student or approving a claim, go through approval steps you set, and every action is logged with who did it, when and why.

    We already have a chatbot. What's actually different?

    A chatbot answers. An agent finishes the job. It recognizes what someone needs from 600+ intents trained on real conversations, answers from your own content, then acts in your systems: creating the lead, sending the Canvas message, writing the credit equivalency, starting the return. When a person is needed, it hands off with a summary so nobody starts from zero.

    How soon will we see results, and how will we prove them?

    We start with one workflow and scope a pilot that can succeed, then prove it on your live funnel against metrics we agree up front: response time, conversion, resolution rate or persistence. New agents start from a tuned template rather than a blank page, so the first one moves quickly. Once the number moves, we expand in stages.

    Is it safe?

    What happens when the agent gets something wrong?

    It's built not to guess. Answers are grounded in your own content, every response is checked for accuracy, grounding and hallucination, and when the agent is unsure it says so or hands off. Agents run in shadow mode first, with your team approving each reply, and a person reviews sampled conversations every week. What we find becomes a content fix or a new intent.

    How do you protect student and customer data?

    Each customer runs in its own private environment on AWS. Personal data is masked before any language model sees it, retention is configurable from 20 minutes to 90 days, and you decide which models may touch which data. We hold SOC 2 Type II, GDPR and HECVAT, with an independent penetration test every year.

    Are you FERPA compliant?

    Our architecture is aligned with FERPA through isolation, data masking and access controls. The formal school-official designation is set up with each institution by contract, and our team can walk your compliance office through the detail.

    Which AI models do you use, and are we locked in?

    We use several leading models and route between them. If one errors or slows, the platform switches automatically, and models are benchmarked monthly on quality, latency and cost. What we own is everything around the model, so you benefit as models improve without re-engineering anything.

    What will it take?

    How much work is this for our IT team?

    Less than most teams expect. Point our web-scraping engine at your site and it keeps your content fresh, with no data pipeline to build. Most popular systems connect from day one, and a small InSync team takes the work from concept through pilot to measurable results.

    Do we have to replace our CRM, LMS or help desk?

    No. Agents read from and write to what you already run, including Salesforce, HubSpot, Canvas, Blackboard, Zendesk, Gorgias and Shopify, always within the permissions you grant.

    How is it priced?

    It depends on the agents, channels and integrations you need, so we scope it with you rather than publish a list price. Most teams start with one workflow, prove the value, then expand.

    What if the agent we need doesn't exist?

    We build it with you. New agents are designed in Agent Studio on the same services, connectors and guardrails as our own, tested in a sandbox and approved before they go live.

    Product Innovation Advisory Council

    Shaped by the people who run these offices.

    We created the council so senior higher-education leaders could compare notes candidly on applying agentic AI to their hardest problems, and directly shape what we build.

    JN
    John NealCouncil moderator · former 2U executive
    AG
    Amanda GulleyChief Product & Experience Officer, ASU EdPlus
    SB
    Dr. Shantanu BoseProvost & Chief Academic Officer, DeVry University
    BH
    Dr. Brenda HarmsVP Enrollment Management, Texas A&M University–Corpus Christi
    JH
    Jay HatcherGlobal Chief Business Development Officer, Risepoint
    PB
    Patrick BennettVP Academic Quality & Dean, Franklin University
    CP
    Charlie ParkerCMO, Keiser University
    KM
    Dr. Karen McGregorExec. Director of Student Success, Purdue Global
    JS
    Dr. Jessica StansburyDirector, Center for AI Learning (CAILI), University of Baltimore
    WE
    Wendy EriksonCEO & Co-Founder, Expert Atlas

    Quarterly 90-minute sessions, plus an annual in-person dinner at ASU+GSV.

    October 2026Governing AI agents

    What it takes for an institution to trust an agent to act on its behalf. Governance is now the council's running theme, and members are co-designing a draft framework with us.

    Guardrails by designInsight to actionPersonalization with equity
    August 2026From answers to action

    What actually makes something an agent, a live first look in an education setting, and where agents can have real impact across the student journey, and where institutions should be cautious.

    What makes an agentAgents in practice
    March 2026Student retention

    First-term intervention strategies, the challenge of fragmented at-risk signals, and early results from AI assistants rolled out across member institutions.

    First-term interventionsAt-risk signals

    What we've heard

    • Trust is earned with evidence. Institutions want to see an agent's work, its data and its logs.
    • Some decisions stay with people. Agents can inform them but should never make them.
    • Offering AI as a choice, not a mandate, drives adoption.
    • At-risk signals are scattered across systems, which slows intervention.
    Get started

    Pick one workflow. We'll show you what it's worth.

    A 30-minute session. We'll map one workflow end to end and show how we'd measure the result.

    Book a demo

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