Connected Intelligence & AI

Businesses don't win by gathering more data; they win by linking it, making sense of it, and taking action based on it. Flow Trixs creates connected intelligence layers that turn random bits of information into clear directions, make intelligence a part of everyday decisions, and spread results throughout your organization.

Who it's for

CIOs, CDOs, CTOs, Operations, and CX leaders who want enterprise-level data foundations, decision intelligence, and AI that can grow with their business.

Results for the business

• Decisions that are faster and clearer across functions
• Less waste in operations and a lower cost to serve
• Predictive visibility into demand, risk, and performance
• Consistent experiences across channels and markets

Data and Analysis

Use all of your data to make your transformation strategy work.

1) Advice on Data and Analytics

• Maturity assessment: people, processes, data, and the platform.
• Use-case portfolio: quick wins and strategic bets ranked by ROI.
• Target architecture: examples of how to use data, analytics, and AI.
• Model of operation: roles, governance, and making changes possible.

Deliverables: a strategy deck, a roadmap for the next 12–18 months, and an investment plan.

Metrics for success: time-to-insight ↓, adoption ↑, ROI per use-case ↑.

2) Data Engineering

• Ingestion and integration: batch/stream, API, files, and CDC.
• Change: quality of data, lineage, and semantic models.
• Lakehouse/warehouse: scalable storage and fast query performance.
• Observability: SLAs, monitoring, auto-healing.

Deliverables: production-ready pipelines and curated data layers.

Success metrics: reliability ↑, latency ↓, cost per GB ↓.

3) The Data Management Office (DMO)

• Policies & standards: classification, retention, access controls.
• Stewardship & catalog: ownership, lineage, searchable assets.
• Quality management: rules, scorecards, automated checks.
• Compliance enablement: audit readiness and regulatory alignment.

4) Science of Data

• Forecasting and optimization: demand, inventory, workforce, and prices.
• Propensity and churn models: acquisition, retention, and LTV.
• NLP and vision: document understanding, search, and inspection.
• Decision-making: testing, modeling uplift, and policy engines.

5) Research and Market Knowledge

• Market scans & benchmarking: category trends, competitor moves.
• Voice of customer: review mining, survey analytics, social signals.
• Opportunity sizing: TAM/SAM/SOM, whitespace analysis.
• Executive insights: signal-to-strategy briefings.

Artificial Intelligence

Add to people's knowledge to open up new opportunities and lasting relationships.

1) Tools and Platforms Powered by GenAI

• Assistants & copilots: search, summarization, drafting, Q&A.
• Document automation: extraction, classification, redaction.
• Knowledge orchestration: retrieval-augmented systems with guardrails.
• Multimodal: text, image, audio — integrated into workflows.

2) Making AI Solutions

• Discovery: identify value cases, fit data, choose models.
• Prototyping: quick tests with real KPIs.
• Hardening: latency, dependability, backups, visibility.
• Rollout: training, change, SLAs.

3) AI as a Service (AIaaS)

• Managed models: lifecycle, updates, monitoring.
• Usage-based pricing: results-linked and scalable.
• Reliability backed by SLA: uptime, response, data residency.
• FinOps controls: cost clarity and optimization.

4) Security for Data and AI

• Zero-trust patterns: least privilege, tokenization, encryption.
• Private inference and isolation for data safety.
• Prompt & content controls; anomaly detection.
• Compliance: enforced policies and audit trails.

5) AI Infrastructure and Engineering

• Platform engineering: feature stores, vector databases, RAG stacks.
• MLOps/LMMOps: CI/CD for models, rollback, drift control.
• Observability: traces, cost meters, safety metrics.
• Portability: cloud, on-prem, hybrid.

6) Ethical AI

• Fairness and bias testing for data and outcomes.
• Explainability and decision transparency.
• Data rights, retention, and consent policies.
• Governance forums for review and accountability.

How We Do Things

• Discover & Prioritize — Map opportunities, define outcomes, align stakeholders.
• Design & Prove — Prototype high-value cases; validate with real data and KPIs.
• Engineer & Secure — Build for scale with governance, reliability, and guardrails.
• Operationalize — Integrate with people and process; measure, learn, iterate.
• Scale & Optimize — Expand coverage, drive continuous improvement, manage value.

Are you ready to connect your data to action?
Let's make your first three high-impact use cases and get one into production quickly.

Begin Your Journey to Connected Intelligence →