About Parity AI
A practical AI team focused on systems, training, and real workflow change.
We built Parity AI for businesses that are tired of generic AI advice and want implementation that fits the way they actually operate. We help teams adopt AI properly, and we build systems that take real work off their plate.
Tahae Mahaki
Co-Founder & Managing Director
Builds AI systems that work in production — RAG pipelines, agentic workflows, and end-to-end automation for businesses that want AI doing real work, not just demos.
Jack Greenlaw
Co-Founder & Head of Operations
Keeps Parity AI running smoothly — from client delivery and programme coordination to the systems and processes that let the team focus on what matters.
Background
Why we started Parity AI
We started Parity AI because we kept seeing the same problem: businesses buying AI tools that never made it past the proof-of-concept stage. The gap wasn't the technology — it was the implementation. Someone needed to bridge the distance between what AI can do and what businesses actually need it to do.
Our work sits at the intersection of AI engineering and business operations. We design and build the pipelines that turn raw data into actionable intelligence — retrieval-augmented generation (RAG) systems that give AI models access to your proprietary knowledge, agentic workflows where AI coordinates multi-step tasks autonomously, and automation pipelines that replace manual processes end to end.
Every system we build runs in production, not in a notebook. That means proper error handling, monitoring, and the kind of reliability you need when AI is making decisions that affect your business.
Why Clients Work With Us
Why businesses choose us over generic AI advice
Implementation First
We care more about whether something works in a real workflow than whether it sounds impressive in a strategy meeting. That is why our training, systems, and content all point back to operational use.
Business Context Matters
We start with the operating reality of the business: the bottlenecks, handoffs, decisions, and information flow. The goal is not AI theatre. It is better throughput, better decisions, and less friction.
Honest Scope
If training is the right answer, we say that. If automation is the right answer, we say that. If you need clarity first, we can help with that too instead of forcing the wrong engagement.
How To Start
Choose the right starting point
Training
Start here when the team needs capability, structure, and practical AI habits.
Explore trainingSolutions
Start here when you already know the workflow pain and want something scoped or built.
Explore solutionsDiscovery Call
Start here when AI matters but you want help choosing the right first move.
Book a discovery callWhat We Build
The kinds of systems and outcomes we work on
RAG Pipelines
Document ingestion, vector embeddings, semantic search, and retrieval systems that give AI models accurate, up-to-date access to your business knowledge. The practical outcome is faster answers, more reliable internal knowledge, and less time lost chasing information across the business.
Agentic Workflows
Multi-step AI agents that research, draft, review, and execute — not just answer questions. From content pipelines to data processing to autonomous monitoring systems, the goal is less manual coordination and more work moving without constant human handoffs.
Automation Pipelines
End-to-end systems that replace manual workflows entirely. Invoice processing, report generation, data extraction, and integration with existing business tools — running on schedule without human intervention and freeing up time for higher-value work.
AI-First Business Design
Helping businesses restructure operations around AI capabilities — not bolting AI onto broken processes, but redesigning workflows where AI handles the heavy lifting and humans handle the judgement calls more effectively.
Proof of Work
What gives this approach credibility
Systems We Use Ourselves
The workflows we teach and the systems we build come from real operational problems we have had to solve in our own businesses and working environments.
Training That Produces Outputs
Our workshops are designed around reusable outputs: action plans, tool shortlists, skill starters, workflow ideas, and rollout guardrails teams can use immediately.
Operational Automation Patterns
The same patterns we teach show up in the systems we build: structured data extraction, workflow automation, monitoring, knowledge workflows, and AI-assisted decision support.
Workflow-Led Delivery
We do not start with a favourite tool and hunt for a use case. We start with the workflow, then choose the right stack for the job and the right entry point for the client.
How We Work
How we approach AI work with clients
We use the same AI tools and workflow patterns we recommend to clients, but the real difference is how we apply them. We test ideas in operating environments, pressure-test what actually holds up, and focus on what a team can realistically adopt or run.
When we work with a client, we start by finding the constraint: what is slowing the team down, where information breaks, and which parts of the workflow are worth improving first. From there, we decide whether the right answer is training, a system build, or a staged path between the two.
Want to talk?
If you already know you want training or a system built, we can point you in the right direction quickly. If you are still figuring it out, we can help with that too.