Common questions about how we work, what to expect, and how PheonIQ delivers measurable results.
Solutions
Training & Team scaling
82% of enterprise leaders claim their organization offers some form of AI training, yet almost 60% still recognise meaningful skills gap.
Access to training and actual capability are two different aspects to consider during adoption.
Our technical competences
Skills our engineers and advisors use to deliver client projects, building technical solutions plus designing governance and change management that makes adoption effective.
AI & Machine Learning
LangChain, LangGraph, Python, PySpark, PyTorch, RAG, LLM fine-tuning, NLP/transformers, Anthropic, OpenAI models
Data Engineering
Snowflake, BigQuery, Azure Databricks, Apache Spark, Hadoop, Data Mesh, Kafka/Flink/Iceberg, SQL/Power, BI
How we help you scale your team
Whether the gap is in your people, skills or in your teams capacity, we can help short term or longterm.
Training Your Team
We can help your team to scale its knowledge. We train your existing people on the job, increasing their competences, ensuring the capability stays in-house.
- Skills assessment against your AI roadmap
- Hands-on workshops and structured training
- Mentoring alongside real projects
Scale Your Team
Adding our specialists directly to your team, bringing the missing skills with them to deliver and maintain the projects for as long as you need.
- Engineers matched to the exact skills you’re missing
- Short-term for a project or deadline
- Long-term as an ongoing extension of your team
AI Solutions & Applications
AI & Data Engineering
Automated data pipelines, data platform setup, document intelligence, knowledge assistants (RAG), forecasting models,process automation
Governance, Change Management & Consultancy
Governance & policy frameworks, change management process , EU AI Act compliance, stakeholder alignment, risk appetite definition; value-stream assessment.
Industries
Manufacturing
healthcare
professional
services
services
retail
FAQs
Do we need to hire new AI teams to support all the solutions we plan to deploy?
Not necessarily. Most organizations don't need a dedicated AI team to sustain agents day-to-day, they need a small number of internal owners, often existing ops or IT staff, trained to monitor performance, handle escalations, and request changes. Larger rollouts across many workflows may eventually warrant a small internal platform team, but that's a scaling decision made once initial deployments prove out, not a prerequisite to get started.
How can we transform the knowledge of our current teams toward supporting AI models?
During implementation, your team works alongside us on real workflows, so they understand how each agent is built and tuned. We document configuration decisions, guardrails, and escalation logic in plain language, then run structured knowledge-transfer sessions before stepping back. The goal is for your internal owners to adjust, extend, and troubleshoot agents independently within the first few months.
Meet us
Schedule a working session with us to identify how we can support you on your journey adopting AI tools and managing your processes with focus on return on your investments.
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