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Generative AI & Agentic Systems
Moving past the prototype. Multi-agent orchestration, tool and MCP server design, retrieval over messy real-world documents, and the evaluation harnesses that tell you whether any of it actually works.
PCC Labs · Est. 2025
The demo works.
That was never the hard part.
Getting a model to answer well takes a weekend. Getting a system that a regulator, an auditor and a customer's security team will all accept takes architecture — tenancy, retrieval, evaluation, audit trails, the boring parts that decide whether you ship. PCC Labs does that part.
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Years architecting enterprise software
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Enterprise firms on platforms I architected
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Products designed and built from scratch
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Production integrations across multiple industries and domains
How a solution architect operates
This is the part that decides whether it works.
A reference architecture for a multi-tenant AI system in a regulated domain — assembled the way we would assemble it for you. Every box below was a decision with a cost. Select one and it will tell you what we traded away, and why.
reference-architecture · multi-tenant agentic system
↳ keyboard accessible: tab into the diagram, then use the arrow keys to move between nodes.
Services
Four ways we work together.
Engagements are scoped tight and delivered senior — no layers, no handoff to a junior bench.
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Solution Architecture
Multi-tenant SaaS done properly: tenant isolation, data boundaries, integration surfaces, and the trade-offs written down before they become expensive. Design reviews for teams who need a second senior opinion.
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Platform Modernization
Legacy .NET estates moved to cloud-native, incrementally. Strangler-fig migrations that keep revenue flowing while the platform underneath changes — because the big-bang rewrite is how these programmes die.
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Fractional Engineering Leadership
For teams that need architectural authority without a full-time hire. Standards, delivery cadence, technical governance, and mentoring engineers into the decisions they will own after the engagement ends.
Approach
Diagnose before prescribing.
Most failed AI programmes were architecture problems wearing an AI costume. We look first.
STEP 01
Diagnose
A short, paid discovery. We read the code, the constraints and the org chart, then tell you plainly what the real bottleneck is — even when the answer is "you do not need AI for this."
STEP 02
Architect
A written design your team can build against: boundaries, data flow, failure modes, security and tenancy posture, and the trade-offs we rejected and why.
STEP 03
Ship
We build the hard part with your team, not instead of them. You keep the system, the reasoning, and the ability to extend it once we are gone.
About
Thirteen years of building the unglamorous parts.
PCC Labs is led by Muhammad Haris Khan, a Solutions Architect who has spent his career in domains where software failing quietly is not an option — enterprise valuation platforms, defence and maritime systems, and large marketplace products.
The platforms he has architected sit underneath hundreds of enterprise firms and tens of thousands of professionals who use them to do their day job. That work is mostly invisible: tenancy models, audit trails, integration contracts, PII handling, and the migration paths that let a fifteen-year-old codebase keep earning while it modernizes.
More recently that has meant production agentic AI — orchestration, tool servers and retrieval over documents that were never designed to be machine-readable. PCC Labs exists to do that work for other teams, at the senior end, without a consultancy pyramid attached.
Contact
Tell us what is breaking.
The most useful first message is a specific one — the system, the constraint, and what "good" would look like. You will get a reply from Haris, not a sales sequence.
Prefer email? contact@pcclabs.com