Gradient Labs pricing: TCO and per-resolution economics for enterprise teams
Gradient Labs pricing TCO models for enterprise teams covering platform fees, per resolution costs, and channel expansion budgets.
TL;DR: Gradient Labs uses an outcomes-based, per-resolution model with no platform fees, but does not publish per-resolution rates or volume tier structure. Enterprise CX leaders must model the full 24-month TCO covering platform licensing, deployment services, integration work, compliance audits, and channel expansion before committing. GetVocal provides an outcome-based pricing model across voice, chat, email, and WhatsApp with EU AI Act compliance built into the architecture from day one. Contact GetVocal for pricing details. CX leaders in regulated industries requiring EU AI Act compliance documentation, transparent governance, and a confirmed deployment timeline should prioritize GetVocal. Teams with simpler use cases and no hard compliance constraints may find Gradient Labs worth evaluating, provided they can obtain written confirmation of base fees, per-resolution rates, and professional services costs before advancing procurement.
Outcomes-based pricing looks straightforward on paper. No platform fee, payment tied to successful resolutions, vendor incentives aligned with deflection performance. The gap between that headline model and the actual 24-month cost is where enterprise budget models break down. Integration services, voice channel onboarding, compliance audit costs, and the ongoing AI optimization required to move deflection from a basic-chatbot baseline to 65-70% (company-reported) each add material spend that the per-resolution rate does not capture. Those line items are where budget surprises originate.
This guide models the full 24-month TCO for enterprise AI agent deployments, calculates cost-per-contact economics at realistic volumes, and compares Gradient Labs' approach with GetVocal's transparent pricing structure.
#Gradient Labs pricing: The core model explained
Gradient Labs charges per successful query resolution rather than per seat or per conversation, targeting financial services (lending, disputes, and KYC) for banks and fintechs. GetVocal's industry footprint spans telecom, banking, insurance, healthcare, retail, ecommerce, and hospitality, giving enterprise buyers outside financial services a broader deployment track record to evaluate. The shift from per-seat to outcomes-based pricing is a positive development for enterprise buyers because it aligns vendor incentives with your deflection goals. If the AI doesn't resolve the query, you don't pay. GetVocal operates on the same principle with an outcome-based pricing model that charges per successfully resolved interaction.
#Calculating Gradient's base fees
Gradient Labs explicitly states they charge no platform fees. Their pricing page confirms an outcomes-based model where you pay only for successful query resolutions. Unlike GetVocal, whose pricing is available on request, the per-resolution rate itself is not published and requires direct vendor engagement to confirm. For enterprise procurement teams building 24-month budget models, this creates an immediate planning gap. Request written pricing confirmation covering per-resolution tiers and minimum annual commitments before advancing procurement.
#Modeling your resolution costs
A "successful query resolution" sounds straightforward, but you need the billing definition in writing before the contract lands on your desk. Key questions to resolve with any outcomes-based vendor:
- Does resolution require complete task completion, or does partial deflection count?
- How are escalations to human agents billed when the AI initiates the handoff?
- Are multi-turn conversations billed per session or per turn?
- What happens to billing when the AI misroutes and the customer contacts you again within 24 hours?
GetVocal's Context Graph architecture defines resolution at the use-case level, with each conversation path audited step by step, making billing disputes straightforward to investigate. Platforms running opaque LLM decision stacks create ambiguity that compounds at invoice time.
#Volume discount thresholds
You won't find Gradient Labs' volume tiers published anywhere. Gradient Labs does publicly describe a complexity-based pricing dimension: higher per-resolution prices for more complex query types, on the basis that resolving a lending dispute or a KYC query delivers more value than a simple balance inquiry. That model introduces a variable the article's flat-rate calculations cannot absorb without confirmed per-query rate data for each complexity tier in your use-case mix.
GetVocal's flat per-resolution rate across all channels and volumes removes that variable entirely, because the unit cost holds regardless of whether you process 50,000 or 500,000 interactions monthly or whether the resolved interaction is a password reset or a billing dispute. For contact centers managing diverse use-case portfolios and seasonal volume spikes, flat-rate pricing simplifies both financial modeling and mid-contract budget forecasting.
#24-month TCO calculation for enterprise deployments
CFOs reviewing AI investment proposals require a 24-month model covering all cost categories, not just the recurring per-resolution fee. Platform subscription fees, deployment services, integration, optimization, and compliance all contribute to total 24-month spend. Those categories are where budget surprises originate.
#Platform licensing in your 24-month TCO
GetVocal's platform licensing produces a fixed 24-month recurring base cost before resolution fees. Contact GetVocal for confirmed figures. At 100,000 monthly contacts with a 65% deflection rate (company-reported), you resolve approximately 65,000 interactions monthly. Your savings run parallel: ContactBabel places the typical cost of an inbound call at approximately $7.20 in the US. Deflecting 65,000 contacts monthly at even a conservative human cost estimate produces substantial monthly labor savings. Use your confirmed per-resolution rate and actual cost-per-contact figure to calculate how long that savings differential takes to offset the resolution fee.
For Gradient Labs, the equivalent calculation requires confirmed per-resolution rates the company does not publish. Budget conservatively using your current cost-per-contact figure from your contact center operating budget and apply your specific volume assumptions to stress-test the model before seeking procurement approval.
#Deployment services cost breakdown
You should budget for initial implementation covering professional services, integration work, knowledge base preparation, and initial agent training. Glovo had its first live agent within one week, scaling to 80 agents in 12 weeks with a 5x uptime improvement and 35% deflection increase (company-reported). That benchmark matters for finance leaders because it defines a realistic implementation runway rather than the 9-14 month timelines many vendors understate during sales cycles.
Gradient Labs describes its deeper implementations as a "project team" approach to define procedures and integrate data, targeting automation of 80-90% of total handling time. That model signals a professional services dependency that may not appear in the per-resolution rate, confirm whether project team engagement is included or billed separately.
#Integration costs by CCaaS platform
Connecting conversational AI to your Genesys Cloud CX, Five9, Avaya, and more involves API setup and bidirectional data sync with your CRM. Custom integrations beyond standard connectors may require additional professional services per integration point. When you're running multiple CCaaS, CRM, knowledge base, and workforce management platforms simultaneously, these costs compound quickly.
GetVocal's pre-built integrations allow teams to work within familiar workflows without custom development retainers. Our "no developer on retainer" deployment model reduces the ongoing custom development dependency that manual platforms require.
#Operational AI optimization costs
Achieving 65-70% deflection (company-reported) requires continuous optimization after deployment, not a one-time configuration. In practice, ongoing optimization work draws on dedicated staff time for performance review, monitoring tooling to surface degradation in deflection or sentiment, and structured testing to validate changes before pushing to production.
GetVocal's built-in continuous learning model reduces this cost because the platform's Context Graph updates from human supervisor feedback through the Control Tower rather than requiring manual prompt rewriting or full model retraining. That distinction cuts the ongoing optimization budget and reduces the FTE dependency that manual platforms require.
#Deployment TCO range
A 24-month TCO model is only as useful as your understanding of what drives variance in each cost category. Use the framework below to scope your internal estimate before each vendor call, then validate against confirmed figures.
| Cost category | What drives variance | Confirm in writing |
|---|---|---|
| Platform licensing (24 months) | Minimum commitment length, prepayment terms, whether the fee scales with deployed agent count or stays flat | Any mid-contract price escalator and renewal terms |
| Implementation and professional services | Number of use cases in scope, process documentation quality, training scope | Fixed-fee quote vs. time-and-materials, training bundling |
| Integration (CCaaS and CRM) | Pre-built connector availability, custom field mapping, bidirectional sync scope | Whether your specific CCaaS and CRM are named on the connector list |
| Ongoing optimization (24 months) | Manual prompt rewriting vs. automated learning, in-house FTE requirements | Whether A/B testing infrastructure is included or billed separately |
| Resolution fees | Monthly contact volume, deflection rate achieved, channel mix | Per-resolution rate, channel parity, and volume tier thresholds |
Platform licensing is a fixed recurring cost confirmed during vendor engagement. Implementation, integration, and optimization vary by deployment scope and should each return a written quote, not a range. Resolution fees are best modeled separately by multiplying your current monthly contact volume by each vendor's confirmed per-resolution rate at your target deflection rate.
GetVocal includes pre-built connectors for major CCaaS and CRM platforms within standard implementation, and Control Tower supervisor feedback updates the Context Graph without manual model retraining, which reduces the in-house optimization FTE dependency that prompt-based platforms typically require. GetVocal also applies the same per-resolution rate across voice, chat, email, and WhatsApp, so your channel mix at month 12 and month 24 does not change the unit cost in your model.
Gradient Labs charges no platform fee and has not published its per-resolution rates or volume tier structure. Apply the same framework, but require written confirmation of all five line items before submitting the model for procurement sign-off.
#Calculating your true cost per contact
The business case for enterprise AI ultimately comes down to unit economics: what does one resolved customer contact cost under AI automation versus under human handling?
#Unit economics: Cost per resolution
ContactBabel places the average cost of an inbound call at $7.20 in the US. Use your actual cost-per-contact figure from your contact center operating budget rather than an industry average, as costs vary significantly by market, channel mix, and labor structure. GetVocal charges a flat per-resolution rate across all channels, making the savings calculation straightforward once you know your human cost per contact and GetVocal's confirmed rate.
High deflection rates require AI that handles complex transactional interactions, not just FAQ lookups. LLM-based agents handle approximately 5-10% of CX interactions (basic Q&A and simple lookups). GetVocal's Context Graph architecture handles the full spectrum including billing disputes, eligibility checks, post-sales documentation, and field service assistance, which is what produces 65-70% deflection (company-reported) rather than lower rates that basic chatbots typically deliver. Basic chatbots limited to FAQ lookups typically deliver 20% deflection or lower. At 100,000 monthly contacts, that produces 20,000 resolutions versus approximately 65,000 at GetVocal's 65% deflection rate (company-reported). Choose your deflection ceiling carefully during vendor evaluation, and require each vendor to provide production deflection data from deployments comparable in complexity to your use cases.
#Model your volume break-even
Use this framework to calculate your break-even point:
- Monthly deflected contacts: Total monthly contacts multiplied by target deflection rate
- Monthly savings from AI: Monthly deflected contacts multiplied by (your human cost per contact minus GetVocal's confirmed AI cost per resolution)
- Break-even months: Total implementation investment divided by monthly savings
At 100,000 monthly contacts with 65% deflection (company-reported) and a conservative €8 human cost per contact, 65,000 deflected contacts multiplied by the difference between your human cost and GetVocal's confirmed per-resolution rate produces substantial monthly savings. Use your specific cost per contact and GetVocal's confirmed rate to calculate precise break-even timelines for your deployment.
#Budgeting for voice and chat channel growth
Omnichannel expansion is where single-channel pricing creates budget surprises. A platform that prices voice differently from chat, or charges a premium for WhatsApp integration, produces a very different TCO once you expand beyond your initial deployment channel.
#Voice platform go-live costs
Voice integration requires telephony infrastructure connection, text-to-speech and speech-to-text capability, and latency optimization for real-time conversation. These requirements add integration costs that chat-only deployments avoid, and some platforms pass those costs through as higher per-resolution rates on voice channels. Confirm your vendor's voice pricing in writing before committing to a channel expansion plan.
#Chat integration TCO breakdown
WhatsApp Business API integration, web chat deployment, and email automation each carry distinct integration costs. WhatsApp requires a Business API provider relationship with associated per-message fees that stack on top of AI platform costs. For regulated industries, compliance requirements under EU AI Act Article 50 (AI disclosure obligations) apply at the system level and must be confirmed during initial deployment. We built GetVocal's compliance architecture for regulated industries to support Articles 13, 14, and 50 requirements across all channels simultaneously.
#Incremental pricing per additional channel
GetVocal charges a flat per-resolution rate across voice, chat, email, and WhatsApp with no channel-specific premium. Contact GetVocal for pricing details. That unified rate means your TCO model holds regardless of whether a customer contacts you by phone or WhatsApp. When you expand from chat to voice, your cost per resolution does not change. Build your 24-month model with your expected channel mix at months 12 and 24, not just your initial deployment channel, to avoid a budget revision mid-contract.
#Gradient Labs TCO vs. other AI platforms
#Evaluating platform base fees
GetVocal's base fee is available on request. Gradient Labs explicitly charges no platform fees, applying per-resolution pricing only. The per-resolution rate is not published, so require written confirmation from the vendor before building your budget model. For CFO-level budget approval, an undisclosed per-resolution rate creates forecasting risk. Request a minimum contract value and confirmed per-resolution pricing from any vendor before advancing to procurement sign-off.
#Per-resolution vs. per-seat pricing models
Per-seat pricing (a fixed monthly cost per agent account) offers one genuine advantage: predictable monthly spend regardless of contact volume, which simplifies budget forecasting for finance teams managing fixed cost structures. The limitation is incentive misalignment: the vendor earns the same revenue whether your agents resolve queries efficiently or not, so there is no commercial pressure on the vendor to improve deflection performance after the contract is signed. Per-resolution pricing corrects that misalignment by tying vendor revenue to successful outcomes. GetVocal's outcome-based model applies this transparently, charging a fixed rate for each resolved interaction confirmed during vendor engagement. When the AI reaches a decision boundary it can't handle, it escalates to a human agent who can guide the interaction, then reassign back to the AI with full context. Humans are in control, not a backup. That structure motivated the continuous improvement that drove Glovo's 35% deflection increase in weeks.
#Hidden integration costs to avoid
The most common source of budget overruns in AI deployments is custom development work that vendors present as standard implementation. Warning signs include:
- "Project team" engagement language without a fixed professional services quote
- "Custom integration" required for your CCaaS platform rather than a named pre-built connector
- Voice capability listed as a separate module rather than part of the base platform
Our "no developer on retainer" deployment model means Context Graph creation, CCaaS integration, and channel onboarding are included in implementation. For enterprise contact center evaluations, this is a meaningful TCO differentiator that reduces total 24-month spend materially.
#TCO comparison at 50K, 100K, 250K monthly contacts
Volume changes AI deployment economics in two directions at once. Resolution fees scale linearly with deflected contacts. Platform licensing, implementation, and integration amortize more efficiently as volume grows. The table below models the human-handling cost you avoid at each volume tier, which gives you the savings side of the equation before applying each vendor's confirmed per-resolution rate.
| Monthly contact volume | Deflected contacts at 65% (company-reported) | Annual deflected contacts | Annual human cost avoided at €8 per contact | Typical deployment shape |
|---|---|---|---|---|
| 50,000 | 32,500/month | 390,000 | €3.12M | Single use case pilot, initial channel deployment, single-region scope |
| 100,000 | 65,000/month | 780,000 | €6.24M | Two to three use cases, omnichannel, paired-language |
| 250,000 | 162,500/month | 1,950,000 | €15.6M | Enterprise rollout, multiple use cases, multi-region, full omnichannel |
Note: The savings figures above use €8 as a conservative European cost-per-contact estimate. Replace this with your actual figure from your contact center operating budget for a precise model. To complete the comparison, subtract each vendor's annual resolution fees and 24-month platform plus implementation costs from the human cost avoided.
#Modeling full costs: Avoid budget surprises
Two cost categories routinely escape initial budget models in European enterprise deployments: agent training and attrition management, and compliance audit costs. Both are real and material.
#Mitigating agent attrition through training
When AI handles routine interactions, the remaining human workload shifts to emotionally complex and technically difficult contacts. Without adequate training, agent attrition can accelerate. Budget for change management, role reframing, and structured training on working alongside AI before deployment, not after attrition spikes.
GetVocal's Control Tower Supervisor View lets supervisors monitor live AI and human agent interactions simultaneously, intervene in any conversation in real time, and provide targeted feedback to improve AI behavior. That capability makes coaching practical at scale and gives human agents a clear role in improving AI behavior. You can see the Control Tower in action in the PolyAI vs. GetVocal comparison, which demonstrates how the Supervisor View differs from a passive analytics dashboard.
#Compliance audit and legal review costs
This is the category most enterprise AI budget models exclude entirely, and in regulated European markets it represents one of the largest cost items. For conversational AI systems classified as high-risk under the EU AI Act (which can include certain use cases in banking, insurance, and healthcare such as credit decisions or eligibility determinations), initial compliance costs cover quality management setup, conformity assessment, and technical documentation.
We engineered GetVocal's architecture for alignment with EU AI Act Articles 13, 14, and 50, with compliance support including SOC 2, GDPR processing capabilities, and on-premise deployment options available. Platforms that retrofit compliance after the fact face the full cost of independent conformity assessment, technical documentation, and legal review. When compliance is built into the architecture from day one, you eliminate most of those incremental audit costs before the first invoice arrives.
#Optimizing for lower per-resolution costs
Deflection rate improvement after launch is the most powerful lever for reducing effective cost per contact over 24 months. GetVocal's human-AI flywheel model means supervisor interventions through the Control Tower improve the AI's handling of scenarios in future interactions. Glovo's deployment demonstrates this: deflection improved 35% within weeks of initial deployment as the system learned from human feedback (company-reported), with the platform scaling across multiple use cases including partner registration and operational support.
#Investment payback: Modeling breakeven point
Time-to-value is a procurement variable that CFOs and CX leaders weight differently. CFOs want payback within 12-18 months. CX leaders need visible KPI movement within 90 days to maintain executive credibility. Both requirements are achievable with the right deployment structure.
#Time to first resolution
GetVocal deploys in 4-8 weeks from contract to first agent in production, covering integration work, Context Graph creation, agent training, and phased rollout using pre-built CCaaS and CRM connectors. Glovo's first agent was live within one week, setting the lower bound for simple use cases with clean data.
Gradient Labs offers a genuinely fast start for teams already on Intercom, Zendesk, or Freshdesk: their pricing page states you can experience value on day one without technical integrations, with 20-50% resolution rates immediately available. That is a real advantage for teams that want to validate the model before committing to deeper implementation.
The deflection ceiling is where the contrast matters. Gradient Labs' day-one rate of 20-50% covers simpler, higher-confidence queries, while GetVocal targets 65-70% deflection (company-reported) from week one, including complex transactional interactions that simpler integrations cannot reach. Reaching Gradient Labs' 80-90% automation target requires their "project team" implementation, which extends the timeline and carries professional services costs to confirm in writing. Request a written timeline from any vendor specifying what use-case scope is covered at day one and what additional work is required to reach their stated automation ceiling.
#ROI milestones by deployment type
Cloud deployments reach first ROI faster because pre-built connectors reduce integration work and there is no infrastructure provisioning cycle to manage. On-premise deployments add a provisioning phase but provide data sovereignty for banking and healthcare customers with strict internal data residency requirements, and can be structured to meet GDPR data processing obligations. Your deployment choice affects your payback timeline by four to eight weeks in most cases. Build that variance into your ROI milestone model before board presentations so your 12-month payback projection holds regardless of which deployment architecture compliance requires.
#Ready to model your TCO?
The per-resolution economics only tell part of the story. Platform licensing, integration scope, compliance costs, and channel mix all move the 24-month number in ways that a rate card alone cannot capture.
Schedule a 30-minute technical architecture review with our solutions team to assess integration feasibility with your specific CCaaS and CRM platforms and return a confirmed cost model before your procurement deadline, or request a demo to see the Control Tower, Context Graph, and omnichannel deployment in production, and benchmark GetVocal's deflection performance against your current contact volume and use-case mix.
#FAQs
What is the standard base fee for GetVocal?
GetVocal's base platform fee covers platform access, the Control Tower (Operator and Supervisor Views), Context Graph management, and omnichannel support across voice, chat, email, and WhatsApp. Contact GetVocal for confirmed pricing and contract terms.
What counts as a billable resolution?
A billable resolution is typically defined as a customer interaction the AI agent successfully completes without human agent takeover, though the exact definition varies by contract. Confirm the precise billing definition with GetVocal during contract negotiations, including how partial completions, AI-initiated escalations, and repeat contacts within a defined window are treated.
Are there volume minimums for per-resolution pricing?
GetVocal requires a minimum 12-month contract, and the per-resolution rate applies uniformly across all channels and volume tiers. Contact GetVocal for confirmed pricing. Gradient Labs does not publish minimum volume thresholds, so require written confirmation from the vendor.
What is the realistic implementation duration and total investment?
GetVocal deployment runs 4-8 weeks from contract to first agent in production. Platform licensing is confirmed during vendor engagement. Implementation, optimization, and integration costs vary by deployment scope. Request a personalized TCO estimate that includes all cost categories plus volume-based resolution fees at GetVocal's confirmed per-resolution rate.
How does pricing work during seasonal volume fluctuations?
GetVocal's flat per-resolution pricing means high-volume months cost more but deliver proportionally higher savings versus human handling. Model your highest-volume quarter for worst-case monthly cost and confirm whether any volume-based adjustments apply during contract negotiations.
Request a personalized TCO review built against your contact volume, CCaaS platform, and channel mix. You can also review Glovo's implementation timeline and KPI progression in the Creandum case study to benchmark a realistic 12-week deployment before finalizing your evaluation.
#Key terms glossary
TCO (total cost of ownership): The full lifecycle cost of acquiring, implementing, operating, and maintaining an enterprise software system, including platform licensing, implementation services, integration work, ongoing optimization, compliance costs, infrastructure, training, and maintenance fees. Enterprise AI investment models typically evaluate TCO over 24-36 months for CFO-level approval.
Context Graph: GetVocal's graph-based conversation protocol encoding business rules, decision boundaries, and escalation triggers into transparent, auditable paths. Created before AI deployment to ensure glass-box governance.
Control Tower: GetVocal's operational command layer providing real-time visibility and control over AI and human agent performance. Enables human-in-the-loop governance at scale with intervention capabilities and auditable oversight.
SOC 2 Type II: An independent audit confirming that a vendor's security controls operate effectively over a defined period, typically required by enterprise procurement and legal teams.