We design and implement AI-driven configurations and agentic workflows that understand your customers, talk to your systems, and execute real actions — with guardrails, observability, and human control built in from day one.
Most AI pilots start with a generic chatbot and stall out when they hit real workflows. We start with your operations: queues, SLAs, escalation paths, tools, and risk tolerance — then design AI agents that live inside that reality.
We use structured outputs, tool-calling patterns, and robust configuration to ensure each AI decision is traceable and reversible. The agent doesn’t “hallucinate a workflow” — it executes clearly defined steps with your systems.
The result is AI that can safely take work off your team’s plate: classification, enrichment, hand-offs, updates, and even end-to-end flows — while keeping humans in control of the edges that truly need judgment.
We don’t just plug in an LLM — we re-think how your configuration works with AI as a core layer:
You get AI that’s deeply embedded in your CX stack — but still governed, observable, and aligned with your operations.
From early use-case selection to production-grade deployment — our process is built to avoid science projects and deliver real, measurable impact on your CX metrics.
We map your workflows, identify high-impact candidate use cases (triage, routing, summarization, actions), and align on risk levels, approval logic, and success metrics.
We define your agentic architecture: tools it can call, systems it can update, guardrails, and how it feeds decisions back into Zendesk and your other platforms.
We implement the agents and AI-driven configs in a non-production environment, run realistic simulations, and iterate until we’re hitting accuracy, safety, and latency thresholds.
We launch with human review and approvals where needed, collect feedback from agents and leads, and gradually increase autonomy as confidence rises.
Once performance is proven, we harden monitoring, logging, and alerting, expand to new queues or brands, and integrate AI-driven signals into your reporting stack.
As your products, policies, and data evolve, we tune prompts, models, and workflows — under a governance framework your stakeholders can trust.
Think beyond a chatbot. We help you deploy AI agents that take on real operational work while staying secure, explainable, and aligned with your CX strategy.
Automatically classify, prioritize, and route tickets based on full conversation context, customer profile, and history — feeding into the same queues, skills, and SLAs you use today.
Configure AI agents that can call APIs, update records, trigger workflows, and assemble responses — with clear rules on when they can act autonomously vs. require human approval.
Automatic conversation summaries, QA assistance, and structured insight extraction (reason for contact, sentiment, root cause) to level up reporting and coaching.
Agentic AI only works when it’s grounded in real systems, policies, and constraints. Our team combines deep Zendesk and CX operations experience with hands-on AI engineering.
Our job is to move you from slideware and pilots to AI that quietly runs in the background — improving handling time, quality, and consistency — without creating new operational risk.
We’ll help you choose the right starting point, design the right guardrails, and build a roadmap that compounds value rather than chasing the latest AI headline.
If you’re serious about using AI to change how work gets done in support — not just to add another widget — this is built for you.
You’re dealing with large ticket volumes and complex routing, and want AI to take over triage, enrichment, and repetitive actions without breaking SLAs.
You’ve experimented with AI replies and FAQ bots, and now want deeper operational impact — AI woven into how work actually moves through your systems.
You need AI that respects data boundaries, access controls, and compliance rules — and you want a partner who can design around those constraints from day one.
Share a bit about your current stack, volumes, and goals, and we’ll propose an agentic AI roadmap — including priority use cases, architecture options, and how to de-risk a production rollout.
Talk to an AI architecture expert