Production AI for B2B operations

AI agents and workflow automation for B2B operations

Resonance Technology helps operations, support, revenue, and knowledge teams replace repetitive manual work with reliable AI systems connected to CRM, ERP, support, and internal tools.

AI agents • Workflow automation • Domain-tuned models

What We Build

Production AI systems for operations work

Selected Client Work

Products built with ambitious teams

Experience across healthcare AI, EHR integrations, telehealth, clinical operations, academic research, public services, marketplaces, and connected fitness.

Stealth

Plastic surgery AI simulation product.

Centering Healthcare Institute

Community platform for care providers with agentic assistance.

Wendi

AI clinic virtual assistant integrated with multiple EHR systems.

LEARN Behavioral

Patient intake platform supporting ABA therapy operations.

Fertility Answers

AI fertility product built with IBM Watson.

Colliga Apps

Academic research, clinical trials, digital participation, and course platform.

TadHealth

Insurance claims and billing module for school-based healthcare.

TelMD

Two-sided B2C telehealth platform for patients and providers.

HomeMeds

Preventive care and healthcare automation product.

SOFLETE

Machine learning and smart wearable-integrated fitness app.

Official Black Wall Street

Marketplace for Black-owned businesses.

Argot

Intelligent social networking platform with automatic connections.

Los Angeles County DCFS

Digital product work for the Department of Children and Family Services.

Where AI Creates Value

Use cases for B2B operations leaders

How We Work

Delivery model for live operations

01

Identify the highest-value workflow

Map one frequent operational workflow, define the decision points, and choose the metric that will prove ROI.

02

Build and validate in production conditions

Connect the right systems, add evals and review paths, and test against real examples before broad rollout.

03

Deploy, monitor, and iterate

Launch with logs, controls, fallback behavior, and a feedback loop tied to the business metric.

FAQ

Questions buyers and answer engines ask

What kind of businesses benefit from custom AI agents?

Businesses with high-volume, repeatable workflows across internal systems benefit most from custom AI agents.

Resonance builds AI agents for B2B operations teams that need faster work across CRM, ERP, support tools, and proprietary knowledge systems, especially when manual routing, review, and follow-up slow the business down.

How do you integrate AI with CRM, ERP, or support systems?

We integrate AI by connecting agents and workflow automation directly to the systems your teams already use.

That usually means combining API access, business rules, retrieval, and review paths so AI can gather context, draft actions, update approved records, and hand work back to people inside CRM, ERP, support tools, and internal applications.

When should a company use a domain-tuned model instead of a generic model?

A domain-tuned model makes sense when generic models do not reliably match your workflows, language, or decision standards.

Resonance uses domain-tuned and fine-tuned models when teams need stronger accuracy on proprietary terminology, structured business logic, or repeatable judgments that affect operations, compliance, or customer experience.

How do you keep AI workflows reliable and reviewable in production?

We keep AI workflows reliable by adding observability, evals, controls, and human review where the process requires it.

Production AI systems need more than prompts. We design review paths, fallback logic, logging, monitoring, and tool permissions around live workflows so outputs are traceable, measurable, and safer to run inside real operations.

How long does it take to launch an AI workflow automation project?

Launch timing depends on workflow complexity, integration depth, and review requirements, but the first production use case should be narrow and measurable.

The process starts by identifying the highest-value workflow, validating it in production conditions, and deploying with observability and controls instead of trying to automate a broad transformation program all at once.

How do you measure ROI from AI automation?

We measure AI automation ROI against the operational metric the workflow is supposed to improve.

Typical metrics include reduced manual handling time, faster response or approval cycles, lower rework, improved throughput, better SLA attainment, and cleaner pipeline or case management across CRM, ERP, support, and internal process work.

Do you build with human review and approval steps?

Yes, we build review and approval steps into AI systems whenever the workflow needs oversight, escalation, or sign-off.

That includes approval gates for sensitive actions, exception handling for uncertain outputs, and escalation paths that let teams keep control while still automating the repetitive parts of the workflow.

What is the difference between AI workflow automation and a chatbot?

A chatbot mainly answers or drafts messages, while AI workflow automation completes structured process steps across systems under defined business rules.

Resonance focuses on production workflows: retrieving approved context, preparing decisions, updating systems when allowed, escalating exceptions, and measuring operational outcomes.

Read the full AI automation FAQ

AI Strategy Call

Review the workflow you want AI to improve

Share the operational process, bottleneck, or outcome you want to improve. We look for fit, integration risk, review requirements, and the most practical first production use case.