Scaler Technologies_
    [RESULTS]_Results

    The kind of impact the right systems drive

    The following are illustrative scenarios showing how we approach common problems and the kind of impact these systems drive. They represent the type of work we do, not specific client accounts.

    • [ SCENARIO · HEALTHCARE ]

      Bringing a multi-location healthcare practice to an audit-ready, zero-trust posture

      The situation

      A growing healthcare practice with several locations in the Chicago area, handling sensitive patient data across systems that grew organically — shared logins, flat network access, no real monitoring. Security had been a “deal with it later” item while they scaled.

      The challenge

      Patient data under HIPAA with broad, unmonitored access is both a compliance exposure and a breach risk. A single compromised login could reach everything — and they'd have no way to detect it if it happened.

      What this kind of build looks like

      A zero-trust redesign: least-privilege access so each role only reaches what it needs, secret rotation, continuous scanning, and automated detection and response across locations and remote endpoints. Security built into the infrastructure rather than bolted on after the fact.

      The kind of impact it drives
      • Access surface dramatically reduced — one compromised account no longer reaches the whole system
      • An audit-ready HIPAA posture established proactively, not after an incident forces it
      • Threats detected and contained automatically instead of going unnoticed

      Representative of our Cybersecurity work. → See Cybersecurity services

      01 / 03
      HEALTHCARE
      IDENTITYPOLICYSERVICESDATADETECTIONAUTHJITCLINICIANSMFA · SSOSTAFFMFA · SSOVENDORSSCOPEDPOLICY ENGINERBAC + ABAC · LEAST PRIVILEGERECORDSPHI · ENCRYPTEDBILLINGPCI · TOKENIZEDSCHEDULINGHIPAAENCRYPTED VAULTAES-256IMMUTABLE AUDIT LOGWORMSIEM · ANOMALY DETECTION24/7 · AUTO-RESPONSE
      ZERO-TRUST ARCHITECTURE · LEAST-PRIVILEGE · CONTINUOUS AUDIT
    • [ SCENARIO · E-COMMERCE ]

      Rebuilding the operating model for a fast-growing e-commerce brand drowning in tools

      The situation

      An Austin-based direct-to-consumer brand that scaled fast and accumulated a tangle of disconnected tools — separate systems for orders, inventory, support, and marketing, none talking to each other, held together by manual exports and one person who knew how it all fit together.

      The challenge

      The tool sprawl was capping growth. Data lived in silos, handoffs broke when someone was out, and onboarding anyone new meant inheriting an undocumented mess. Every new tool added to the tangle instead of reducing it.

      What this kind of build looks like

      A full audit of the operating model, a blueprint for the system that should exist — fewer tools, clean handoffs — then a rebuild into modular, documented infrastructure, with data flowing between systems automatically and a single source of truth replacing the manual exports.

      The kind of impact it drives
      • Redundant tools consolidated — lower software spend and fewer moving parts to break
      • Manual exports between systems largely designed out
      • A documented operating model a new hire can actually step into

      Representative of our Systems Architecture work. → See Systems Architecture services

      02 / 03
      E-COMMERCE
      SOURCESINGESTDATA LAYERSERVICESACTIVATIONNORMALIZELEARNSTOREFRONTWEB · APPADSMETA · GOOGLEMARKETPLACESAMZ · TTEVENT BUS · INGESTIONWEBHOOKS · STREAMSUNIFIED DATA LAYERCUSTOMER · ORDER · INVENTORY · CONTENTINVENTORYREAL-TIMEORDER FLOWOMSSUPPORT AITIER-1FULFILLMENT3PLCRM / LIFECYCLESEGMENTSANALYTICSBI · ATTRIB
      EVENT-DRIVEN PIPELINE · UNIFIED DATA LAYER · REAL-TIME SYNC
    • [ SCENARIO · FINANCIAL SERVICES ]

      Deploying AI agents to qualify and move deals for a commercial lending firm

      The situation

      A Miami commercial lending firm where reps spent most of their day on manual qualification — pulling data, checking criteria, chasing documents — before a deal could even move forward. High-volume, repetitive, judgment-light work that ate the team's time.

      The challenge

      The manual qualification bottleneck meant reps spent more time on admin than on closing, and good leads went cold while they worked through the queue.

      What this kind of build looks like

      A system of AI agents that handle qualification end to end — pulling and checking applicant data against criteria, flagging exceptions for a human, and routing qualified deals into the pipeline automatically. Scoped permissions and audit logs on every agent action, with humans in the loop on the decisions that matter.

      The kind of impact it drives
      • Hours of manual qualification compressed into minutes per deal
      • Reps redirected from admin toward actually closing
      • Faster response while leads are still warm

      Representative of our AI Agents work. → See AI Agents services

      03 / 03
      FINANCIAL SERVICES
      INTAKEENRICHMENTDECISIONINGROUTINGOUTCOMESAUDITSCORENURTURELOGINBOUNDFORMS · ADSREFERRALSPARTNERSOUTBOUNDCAMPAIGNSENRICHMENT · KYC · COMPLIANCEFIRMOGRAPHICS · SANCTIONS · SUITABILITYAI QUALIFICATION AGENTINTENT · FIT · RISK SCORINGAUTO-APPROVEHIGH FITHUMAN REVIEWEDGE CASESREJECT / NURTURELOW FITPIPELINECRMADVISOR DESKESCALATIONIMMUTABLE AUDIT TRAILEVERY DECISION · TIMESTAMP · MODEL VERSION
      AUTONOMOUS QUALIFICATION · HUMAN-IN-THE-LOOP · FULL AUDIT TRAIL

    Want this kind of result in your business?

    Want results like these for your business?

    Tell us a bit about your business — we'll tell you honestly if this is a fit.