Solutions

Emotional Intelligence change how we interact with agents.

uniqOS is helping developers all over the world change how their systems interact with users. Emotional Intelligence is in the frontier of new human/machine coexistence.

01 / Solution

Companion Apps

Apps users come back to

Retention lives or dies on whether the agent remembers who they are. uniqOS gives you a relationship that compounds over weeks, not a chat that resets every session.

↑ retention

The problem

Most companion and consumer AI apps churn because every conversation starts from zero. The agent has no stable identity, no memory of what mattered last time, and no read on how the user is showing up today. Novelty fades within a week.

How uniqOS approaches it

Drop in a persistent personality, a relational memory that consolidates what's meaningful and forgets the noise, and an empathy layer that picks up shifts in tone between sessions. The agent greets returning users like someone who actually knows them — because it does.

Outcomes

  • Higher 7- and 30-day retention without changing the underlying model
  • Longer, more meaningful sessions driven by continuity, not gimmicks
  • Forget about "role playing prompting" in every session

Where it fits

Consumer AIMental wellnessCoachingSocial apps
02 / Solution

Customer service

De-escalate through empathy

Agents that read frustration and modulate accordingly. Fewer human handoffs, higher NPS, lower cost per ticket.

↓ escalations

The problem

Scripted support bots make angry users angrier. They miss sarcasm, ignore rising frustration, and answer the literal question instead of the real one. The result is escalation to a human — at exactly the moment the relationship is most expensive to repair.

How uniqOS approaches it

uniqOS reads the affective state of the interlocutor in real time and modulates tone, pacing and depth without sliding into appeasement. A consistent service persona, calibrated empathy, and memory of prior touchpoints turn one-shot tickets into ongoing relationships.

Outcomes

  • Measurable drop in human escalations on resolvable tickets
  • Higher CSAT and NPS on contained conversations
  • Lower cost per resolution while preserving brand voice

Where it fits

Support automationTelco & utilitiesFintechE-commerce
03 / Solution

Training & simulation

Realistic interlocutors

Train sales, healthcare, mediators and frontline staff against agents that actually behave like the people they'll meet — not generic chatbots reading from a script.

↑ skill transfer

The problem

Roleplay-based training fails when the simulated counterpart breaks character, capitulates too quickly, or never gets emotionally activated. Trainees learn to handle a chatbot, not a human under pressure.

How uniqOS approaches it

Compose simulated personas with stable traits, values and emotional baselines. The empathy layer drives realistic reactions to pressure, ambiguity and rapport — and the relational memory means the same persona behaves consistently across sessions, scenarios and cohorts.

Outcomes

  • Trainees rate scenarios as significantly more realistic
  • Faster skill transfer from simulation to live interaction
  • Reusable persona libraries across teams and certifications

Where it fits

Sales enablementClinical trainingMediation & negotiationFrontline ops
04 / Solution

Service robotics

Sensitivity for embodied agents

Bring an empathic register to humanoids and service robots. The same layer, behind a different body.

↑ acceptance

The problem

Embodied agents fail the social test long before they fail the technical one. A robot that interrupts, misreads hesitation, or addresses everyone the same way gets switched off — regardless of how capable its motion stack is.

How uniqOS approaches it

uniqOS exposes the same personality, empathy and relational memory APIs to whatever lives on the other side — a humanoid, a kiosk, a service robot in a clinic or a hotel. The interaction layer is decoupled from the body, so the same identity travels across form factors.

Outcomes

  • Higher user acceptance and dwell time around embodied agents
  • Consistent character across deployments, fleets and form factors
  • A clear separation between motion, task and relational stacks

Where it fits

HumanoidsService roboticsHealthcare robotsPublic-space kiosks

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