inncivio is an AI agentic layer that sits on top of transaction platforms (trading, crypto exchanges, FX, lending marketplaces, betting/gaming). It reads real‑time user behavior and the platform context graph to surface contextual educational, informational, and actionable guidance so users transact more and better.

Transaction‑driven products: retail and institutional trading platforms, crypto exchanges, foreign exchange (FX)/remittance products, lending marketplaces, and betting/gaming. Any product where user actions convert to revenue is a fit.

Reduce user friction and hesitation by predicting next steps from decision traces and the context graph, then delivering timely guidance or call to actions (CTAs). That increases transaction counts and improves the quality of decisions.

* Decision traces: the sequence of user interactions (clicks, hovers, time on screen) that reveal how a user reached a moment of choice. inncivio learns patterns from those traces.

* Context graph: a structured representation linking user behavior, UI elements, account/profile state and knowledge sources so the system knows “what this user sees and why it matters” in real time.

The agentic layer is inncivio’s runtime intelligence that acts like a lightweight assistant on the product: it observes decision traces and the context graph, decides the right micro‑intervention (information, education, or CTA), and delivers it in the UI without changing the core product.

* Educational: short explanations tailored to sophistication.
* Informational: contextual summaries (portfolio snapshot, event impact).
* Actionable: guided next steps or CTAs (open trade ticket, convert currency, use a tool).

Three proprietary AI models: a UI clustering model to find safe display spots, an LLM+RAG for contextual content, and a reinforcement learning model that uses decision traces to learn per‑user what interventions help. Together they minimize noise and maximize relevance.

* inncivio is a purpose‑built, proprietary AI in‑app guidance system for fintech platforms, not a generic GPT wrapper. From the ground up it connects three pieces: (1) real‑time behavioral inputs (decision traces), (2) a context graph that maps the UI + product state + knowledge base, and (3) an agentic execution layer that chooses and delivers content.

* The system continuously predicts the most useful micro‑intervention and injects it into the UI at the right place and right time. Watch our demo on Interactive Brokers: https://www.loom.com/share/9747a4f803e6403db60ef7a68a83a67b (product deep dive and deliverables are provided during pilot conversations).

* Illustration: two users consider buying Microsoft on the same platform. Sally is a visual learner and has been hesitating; inncivio surfaces a short, tailored video summarizing Microsoft’s partnership with OpenAI - she buys confidently. Mike is an impact investor who reads long‑form news; inncivio surfaces a CTA linking Microsoft’s 2025 sustainability report - he acts immediately. Same moment, same stock - inncivio autonomously delivers the insight that matters to each user.

No, inncivio’s AI continuously learns from user behavior and adapts in real time, eliminating the need for manual updates. Clients do configure initial guardrails, knowledge sources, and tone during setup.

No, default behavior is conservative and non‑intrusive. The reinforcement layer learns each user’s tolerance; items ignored are shown less. Clients set guardrails and tone during setup.

Web: a single line of JavaScript added to your header. Mobile: inncivio provides an SDK (software development kit) roadmap and also an API option so you can control execution/UI. Web integration is the fastest path.

Web/browser integration is lightweight (typically weeks). Pilot setup and 1-2 month(s) pilot is recommended to measure impact. Mobile SDKs require more coordination.

inncivio and the client define KPIs up front. We use historical baselines (e.g., last 6 months) and measure changes in transaction counts, conversion, support tickets, retention and other agreed metrics.

Early pilots and demos have shown low‑double‑digit uplifts in transaction counts (example ~7%). Results depend on traffic, cohort selection, and KPI focus; pilots quantify impact per client.

inncivio ingests anonymized decision traces; personally identifiable information (PII) is not stored. Data is encrypted in the browser and again server‑side. Clients and inncivio agree what screens/data are permitted during setup; sensitive fields can and will be excluded.

inncivio supports regionally isolated deployments (US and EU/AWS regions). Data residency and replication are configurable to meet compliance needs.

Core inference runs on inncivio’s controlled stack (AWS) to reduce latency and exposure. External models may be used for optional tasks under strict zero‑retention controls if a client requests it.

Typical contextual responses in demos are in the ~2-4 second range; exact latency depends on integration and data access. inncivio optimizes for sub‑interactive latencies suitable for real‑time UI nudges.

Encrypted transport (TLS), double encryption for stored artifacts, per‑client instances, and configurable regional hosting. inncivio is SOC2 compliant and supports enterprise audits. Compliance filters and guardrails are applied to content flows to prevent regulatory issues (e.g., removing advice‑like language).

No, PII is retained in user footprints. During the setup, clients choose which pages/fields to include; sensitive data can be redacted or excluded entirely.

Typical steps: 1) contact inncivio at hello@inncivio.com; 2) share sandbox/demo access or provide a demo user account; 3) define pilot KPIs and target cohorts; 4) sign a short design‑partnership scope (non‑binding) to set roles and guardrails; 5) run a 1-2 month(s) pilot; 6) review results and plan roll‑out. inncivio handles most integration work and guides the client through compliance and KPI measurement.