- A Business Unit of Scanlytics Technology (STPL)
- hello@aitrixx.com
- +1 813 556 6568
- +91 989 2444 251
- Global Presence: US · UK · India
AItrixx is the AI & Gen AI implementation unit of Scanlytics Technology. We design and ship AI agents, Model Context Protocol (MCP) integrations and enterprise RAG — from first POC to secure, observable, at-scale deployment.
from aitrixx import Agent, MCP, Retriever
agent = Agent(
model="claude-sonnet",
tools=[MCP("crm"), MCP("erp")],
memory=Retriever("enterprise-rag"),
guardrails=True,
)
result = agent.run("Resolve ticket #4821")
# grounded · auditable · in production
About AItrixx AItrixx is the dedicated Generative AI unit of Scanlytics Technology (STPL). We help enterprises move past demos and chatbots to agentic systems that take real actions on real business tools — grounded in your data, governed by guardrails, and measured with evaluations.
An Anthropic / Claude partner with deep engineering roots — we deliver, we don’t just advise.
Full-stack Gen AI capability under one accountable team.
We optimize for business outcomes, not model benchmarks.
Core Capabilities Agents, MCP, RAG and LLMOps — explore how each one works in production at AItrixx.
Autonomous, tool-using agents that plan, call your systems and complete multi-step work — with human-in-the-loop controls where it matters.
Custom MCP servers that connect models to the systems where your data and tools live — securely, with scoped permissions and full auditability.
Retrieval-augmented generation pipelines that ground answers in your knowledge base, cite their sources and dramatically reduce hallucination.
The operational layer that keeps Gen AI reliable in production — evaluations, tracing, prompt management and cost/quality monitoring.
How We Engage Pick the entry point that fits where you are — advisory, a fast proof of concept, custom build, or fully managed AI.
Use-case discovery, feasibility, ROI modelling and an AI roadmap your leadership can back.
A working proof of concept in weeks — with a clear, de-risked path to production.
Agents, MCP servers, RAG pipelines and LLM apps engineered for your stack and scale.
Ongoing evals, monitoring, tuning and optimization to keep AI reliable and cost-efficient.
Deflect & resolve tickets with grounded, on-brand responses.
Ask your documents, policies and wikis in natural language.
Agents that execute multi-step back-office processes.
Accelerate engineering and analytics teams safely.
Industries We bring production discipline to regulated and data-sensitive sectors.
Compliant assistants, risk & ops automation with audit trails.
Grounded knowledge retrieval with strict PII handling.
Support agents, product discovery and catalog intelligence.
Embedded copilots and AI features inside your product.
Ops automation and document-heavy workflow agents.
Secure, private deployments for sensitive workloads.
How We Work Four disciplined stages that de-risk every AI engagement.
Identify high-value use cases, data readiness and success metrics. Define guardrails up front.
Ship a working POC in weeks against real data, with evaluations proving it actually works.
Harden for security, scale and reliability — MCP integrations, observability and CI for prompts.
Monitor quality, cost and drift. Continuously evaluate and tune as models and needs evolve.
Why AItrixx Hands-on delivery with Claude, the Claude Developer Platform and MCP — aligned to how frontier AI is actually built.
Backed by Scanlytics’ delivery track record — 35+ Splunk integrations and real distributed-systems experience.
Private deployments, PII controls, access scoping and audit trails for regulated environments.
We measure success in resolution rates and cost-to-serve — not model benchmarks or demo wow-factor.
Teams across the US, UK and India — the same group trusted by 135+ enterprise clients.
Claude, OpenAI, Bedrock or Azure — we choose the right model and architecture for your constraints.
Talk to our team about agents, MCP, RAG or an AI roadmap. No pitch — just a straight conversation about your problem and the fastest path to value.