Tonic3
Tonic3
Tonic3
Tonic3
Tonic3
Tonic3
Tonic3 bespoke Azure solutions
Description of the Offer
Tonic3 helps enterprises design, build, and scale practical AI systems—and the agentic workflows that sit on top of them—on Microsoft Azure. We combine user-centered design, enterprise engineering, and disciplined change management to produce outcomes that executives can trust and frontline teams will actually use.
At its core, the offer delivers production-grade AI agents and copilots that automate or accelerate work across revenue, operations, and compliance. These are not novelty chatbots. They are task-oriented systems that integrate with your data, tools, and processes and operate under explicit guardrails, with human-in-the-loop controls where appropriate. We build on the Microsoft Cloud, using services such as Azure OpenAI Service, Azure AI Search, Azure AI Foundry/Studio, Azure Machine Learning, Azure Functions, Azure Kubernetes Service, and Microsoft Fabric—aligned with enterprise security (VNETs, Private Link), governance, and Responsible AI policies.
Key elements of the offer:
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AI Strategy & Use-Case Prioritization. We start by challenging assumptions. Where, specifically, can AI create measurable value in your organization? What should not be automated? We align use cases to business goals, data readiness, control requirements, and realistic ROI thresholds—so you invest where the payoff is most likely.
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Agent Architecture & Orchestration. We design agentic workflows that mirror how high-performing teams already work: retrieve information, reason, decide, act, and record. Agents are decomposed into modular roles (e.g., Researcher, Planner, Executor, Reviewer) orchestrated via Azure Functions/AKS and eventing (Event Grid/Service Bus) with robust observability (Application Insights).
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Human-Centered UX. Our roots are in UX. We deliver interfaces that fit the work: embedded side-panels in Microsoft 365, lightweight web apps, or workflow-triggered automations—so adoption is natural and training is minimal.
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Integration with Existing Systems. Agents don’t live in isolation. We integrate with CRM/ERP, ticketing, data warehouses, and line-of-business apps using Microsoft Graph, Power Platform, and REST/GraphQL connectors. Each action is permissioned and logged.
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Value Assurance & Governance. Every deployment includes KPIs, kill-switches, rollback plans, and a measurable test-and-learn loop. If a use case cannot demonstrate value under real controls, we recommend stopping—before you spend more.
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Operate & Improve. We offer managed services for monitoring, prompt/version governance, drift detection, cost control, and safe model upgrades. The objective is stable, predictable performance—not hype.
Typical solution patterns we implement:
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Revenue & Go-to-Market Agents: SDR/BDR assistants for prospect research, lead enrichment, outreach drafting, qualification summaries, and “meeting kit” generation. These agents reduce manual prep time and improve consistency, while handing off cleanly to sales systems.
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Service & Operations Agents: Case triage, knowledge retrieval, response drafting, and ticket summarization integrated with Microsoft 365 and service platforms. The focus is faster resolution with fewer handoffs.
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Compliance & Risk Agents: Document intake, policy mapping, narrative generation for analyst review, and continuous monitoring of changes—keeping humans in control and audit trails intact.
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Knowledge & Productivity Copilots: Private, role-aware copilots for internal teams, securely retrieving institutional knowledge from SharePoint, Confluence, Fabric, and more.
Customer Need or Pain Addressed
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Work is fragmented and manual. Teams spend time finding information, re-entering data, drafting repetitive communications, and summarizing updates. Variability in quality and throughput is high.
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Knowledge is trapped. Critical know-how lives in files, inboxes, and people’s heads. When people move on, quality drops and onboarding time increases.
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Scaling expertise is expensive. Improving coverage (e.g., more prospects touched, more tickets handled) historically requires more headcount or more outsourcing, with diminishing returns.
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Compliance slows everything down. Controls and reviews are necessary, but they add friction and cost. Leaders are wary of “black box” AI that undermines auditability.