Conversational AI fails in the decisions made before the build: wrong use case and platform, with no plan for accuracy or escalation. We get these calls right because we’ve made them in production. You commit a budget to a plan that’s scoped, de-risked, and ready to ship.
Find where conversational AI creates value in your business, and where it doesn’t.
We turn a scattered set of ideas into a sequenced plan you can fund and defend.
Our team designs the technical approach and chooses the platform on the merits, not on what we’d prefer to sell.
We design the controls that let conversational AI pass a security and brand review.
Test the riskiest assumptions cheaply before committing.
A structured AI discovery rates each candidate’s use case on value and feasibility, so you start with a clear, prioritized view of where conversational AI is worth pursuing.
You receive a sequenced roadmap, a platform and integration architecture, and a governance plan, with a reasoned build-vs-buy decision for each use case.
Where uncertainty is high, a scoped proof of concept tests it against clear criteria. You get a decision grounded in evidence rather than a proposal, and a clear read on whether to scale, adjust, or stop.
Take the plan to your own team, or keep Relevant on for the AI-assisted software development that ships it. Either way, the architects who designed the plan can stand behind the build, with no obligation to continue.
We’ve delivered 246 projects, including production conversational systems. The recommendations you get are shaped by what we’ve shipped, governed, and scaled.
With 92% senior and middle engineers, the people advising you have made these architecture and integration calls before, under real production constraints.
SOC 2, GDPR, and HIPAA constraints shape the strategy from discovery, so the approach you approve is one your security team can sign off on.
Platform and build-vs-buy recommendations are made on the merits. We’ll recommend buying, or not building at all, when that’s the right call.
If you choose to build with us, the people who designed the plan can execute it, and with 96% retention, they stay through it.
A 4.9 Clutch rating from verified clients who consistently cite transparency and delivery quality.
Both, and the second is the point. The engagement produces concrete artifacts:
We design every deliverable so your team, or any vendor, can execute from it without us. You’re paying for a plan you can fund and act on.
We weigh each use case against a few factors:
Commodity use cases with clean requirements often favor buying. Differentiated, deeply integrated, or sensitive use cases often favor building. We show you the reasoning per use case.
When a simpler interface does the job better. If users need a fast, deterministic path — a form, a filter, a status lookup — a conversational layer often adds friction rather than removing it.
Conversational AI earns its place when intent is ambiguous, when users would otherwise navigate complexity manually, or when natural language genuinely reduces effort. Part of our job is telling you which of your use cases actually clear that bar.
We work within controlled boundaries, agree IP and data-handling terms before we start, and don’t use your proprietary data to train third-party models. Where a proof of concept touches sensitive data, we use synthetic or anonymized data, and we map SOC 2, GDPR, and HIPAA constraints into the approach from discovery. The objective is a plan that passes your security review, designed by people who respect it during the work as well.
That’s your choice. Many clients take the roadmap and architecture to their own team and run with it. Others keep Relevant on to build what we designed, which removes the handoff gap between strategy and delivery. The engagement is built to work either way, and nothing in the plan locks you to us.
That’s the conversation to have first. Bring us the use case, and you’ll leave with an honest read on whether it’s worth building, and what it would take.
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