[ Custom Voice AI Advisory & Consulting ]
Decide the right voice AI approach before you build it.
Independent guidance on feasibility, architecture, cost, and build-vs-buy, from a team that ships production voice agents, not slide decks.
Most voice AI budgets are lost before the first call.
The expensive mistakes happen early, before the first call is ever built, and each one is the kind you cannot cheaply undo later. A short advisory engagement de-risks the decisions that everything else depends on, with advice grounded in production implementation, not theory.
- Wrong platform
- A re-platform halfway through the build.
- Wrong cost model
- Economics that collapse at production scale.
- Wrong architecture
- A design that fails the compliance review.
[ What we advise on ]
The decisions that shape the outcome.
Seven areas where an early, outside call changes the budget, the timeline, and whether it reaches production.
Feasibility
Whether voice AI fits the workflow, and where it will and will not hold up.
Architecture
Provider mix, orchestration, fallback strategy, and deployment model.
Cost
Per-minute economics, scaling curve, and self-hosting break-even points.
Build vs buy
Platform selection versus custom build, weighed against your constraints.
Quality risks
Latency, hallucination, interruptions, accents, background noise, and edge cases.
Compliance
HIPAA, GDPR, SOC 2, and data-residency implications of each option.
Roadmap
Pilot scope, success metrics, and the path from prototype to production.
[ Cost modeling ]
Economics that survive contact with scale.
Most voice AI business cases rest on per-minute math that quietly breaks at volume. We model the real curve — providers, fallback, and self-hosting — and find where the numbers actually turn.
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Per-minute reality
True cost across LLM, STT, and TTS — fallback and retries included, not the sticker rate.
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The scaling curve
Where cost per call falls, flattens, or spikes as volume climbs.
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Self-hosting break-even
The exact volume where owning the stack beats paying per minute.
[ When this service fits ]
Where outside judgment pays for itself.
Evaluating voice AI
You are deciding whether to invest in voice AI at all.
Vendor selection
You are comparing platforms, providers, or build-vs-buy.
Cost modeling
You need realistic economics before committing budget.
Architecture review
You have a design and want a second opinion before building.
Compliance risk
Regulated data makes the wrong architecture expensive.
Stalled pilot
A prototype works but will not survive production.
[ What you get ]
Deliverables you can act on.
- A clear feasibility verdict, not a sales pitch
- Reference architecture matched to your constraints
- Cost model with scaling and self-hosting break-even
- Build-vs-buy recommendation with trade-offs
- Compliance and data-residency guidance
- Pilot scope with measurable success criteria
- A prioritized roadmap to production
[ Engagement shapes ]
Engage at the depth the decision needs.
| Engagement | Duration | Best for |
|---|---|---|
| Strategy session | 1 hour | A focused decision: feasibility, vendor, or architecture. |
| Architecture review | Up to 1 week | Validating an existing design before you build. |
| Cost & compliance audit | 1–2 weeks | Pressure-testing economics and regulatory fit. |
| Technical roadmap | 1–3 weeks | Preparing for a pilot or a custom build. |
| Ongoing advisory | Monthly | A technical partner through an internal build. |
[ How we work together ]
From open question to confident decision.
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1–2 days
Frame the decision
Define the question (feasibility, vendor, architecture, or cost) and what evidence settles it.
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1–2 weeks
Assess
Audit the workflow, stack options, economics, quality risks, and compliance constraints.
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2–3 days
Recommend
A clear verdict with the reasoning, trade-offs, and a reference architecture behind it.
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Ongoing
Support execution
Stay on as a technical partner while the decision becomes a pilot or a build.
[ Security & compliance ]
Engineered to clear the compliance review.
[ Proven in production ]
Voice AI we've taken to production.
Two engagements where the early architecture and cost calls decided whether voice AI shipped.
[ Common questions ]
Asked before most engagements.
When consulting instead of development?
Consulting when the decision is not made yet: feasibility, vendor, or architecture. Development when it is, and you need it built.
Can you compare Vapi, Retell, Bland, Twilio, and custom?
Yes, vendor-neutral and weighed against your latency, cost, compliance, and integration constraints.
Can you review our existing prototype?
Yes. We audit why it fails on real calls and what it takes to reach production.
Do you help with cost modelling?
Yes: per-minute economics, the scaling curve, and self-hosting break-even at your volumes.
Can you support our internal team’s build?
Yes, ongoing advisory through the architecture, vendor, and quality decisions along the way.
6 yrs
in complex B2B software
20+
experts across AI, product, design, and engineering
4.9/5
average client satisfaction
5+
industries: SaaS, hospitality, LegalTech, MarTech, support
"What truly stood out was Softcery's deep AI expertise. They were able to take our vision and turn it into a reality, and the final product has exceeded our expectations. Working with Softcery has been a game-changer for our business."
Jeanette Kreft
Managing Director, The Compliance Company & Upskill AI
"Softcery is not your typical software development agency – they're a full-scale product consultancy. The benefit of working with them is the collaboration."
Ryan Tabb
Founder, Bullseye