Scale the function, not the payroll.
When growth outpaces hiring, another full-time req is the slow answer. We stand up a nearshore AI-enabled pod that owns one function end to end, Sales, CS, RevOps, Recruiting, Support, or Finance, moves the KPI, and scales on your signal. One SLA, one bill, one accountable operator. Scope is set in a single working session.
The function is under-performing, hiring is slow, and the AI project never shipped.
Headcount is the wrong lever
You can't hire your way to a 24/7 SDR motion or a same-hour support SLA. Linear cost, linear output, linear ceiling.
AI pilots aren't shipping
Most internal AI projects die because no one owns the workflow change. A model is not a function. A demo is not delivery.
Vendors stack, no one owns
BPO for labor, SaaS for tooling, consultants for design, internal lead for the integration, and the KPI moves nowhere.
We don't sell seats or software. We sell the function, running.
A Nearshore AI Pod is the smallest unit of a function that actually moves the KPI. 3 to 8 nearshore operators, paired with an AI agent stack tuned to your tools and data, under one SLA, owned by a named XCAILE operator. You buy pipeline created, tickets closed, time-to-fill, not labor hours.
Pod design
We map the workflow, instrument the KPIs, and pre-build the AI agents before we hire a single human.
Pod assembly
Nearshore operators selected for the function, time-zone aligned, English-fluent, tooling-native. Trained on your playbooks.
Pod operation
AI handles volume; humans handle judgment, escalation, and exceptions. Weekly QBR, live KPI dashboard, monthly scorecard.
One function. One pod. One SLA.
Sales Development Pod
Outbound research, multi-channel sequencing, AI voice + email, qualification, meeting booking. KPI: SQLs / month.
Customer Success Pod
Onboarding, adoption nudges, QBR prep, renewal motion, churn-risk routing. KPI: NRR, time-to-value.
Customer Support Pod
Tier-1 + tier-2 support, AI deflection, escalation routing, knowledge-base curation. KPI: CSAT, FRT, resolution.
RevOps Pod
CRM hygiene, pipeline reporting, attribution, commission ops, enablement assets. KPI: data quality, forecast accuracy.
Recruiting Pod
Sourcing, screening, scheduling, candidate experience, ATS hygiene. KPI: time-to-fill, pass-through.
Finance Ops Pod
AP/AR, reconciliation, expense, vendor mgmt, monthly close support. KPI: days-to-close, error rate.
From signed scope to function running, in four weeks.
- Week 1Step 1
Map & instrument
Process discovery, KPI baselining, tool access, success-metric contract. You sign off on the operating spec.
- Week 2Step 2
Assemble & train
Pod staffed from our nearshore bench. AI agents trained on your tools, data, and playbooks. Supervisor named.
- Week 3Step 3
Supervised dry-run
Pod runs in shadow against real volume. We tune, you approve, we lock workflows and escalation rules.
- Week 4Step 4
Go live under SLA
Function transitions to the pod. Weekly QBR begins. Live dashboard goes on for you and your team.
Nearshore AI Pod vs the alternatives.
| AI Pod | Build in-house | Traditional BPO | AI SaaS only | |
|---|---|---|---|---|
| Time to function running | About 30 days | 4 to 6 months | 6 to 10 weeks | 1 to 2 weeks setup, no humans |
| Sold as | Outcome / KPI | Headcount | Seats / FTE | License |
| AI + human integrated | ||||
| Time-zone alignment | n/a | |||
| One SLA, one owner | ||||
| Function-level KPIs | depends | |||
| Scales weekly | ||||
| All-in cost vs in-house | Typically lower | Baseline | Sometimes lower | Tool cost only, work still on you |
If the comparison above already reads like your last two hiring cycles, skip ahead.
24h reply · No obligation · NDA on request
A function that moves a KPI, on a predictable line.
At a glance
- Product
- Nearshore AI Pod, function-as-a-service, 3 to 8 operators + AI agent stack.
- Buyer
- Mid-market operators and functional leaders (25 to 500 employees).
- Deployment time
- About 30 days from signed scope to function running under SLA, depending on scope and access.
- Pricing model
- Flat monthly per pod, sized by function and volume. Typically below in-house all-in cost, modelled in your assessment.
- Functions available
- Sales Development, Customer Success, Customer Support, RevOps, Recruiting, Finance Ops.
- Geography
- Nearshore Latin America, time-zone aligned with North American business hours.
- Governance
- Named XCAILE account lead, weekly QBR, monthly scorecard, live KPI dashboard.
- Security
- Documented security and access controls, signed DPAs, least-privilege access via your IdP.
- Upgrade path
- Add pods, expand pod size, or layer global employment and compliance for international expansion.
- What's billed
- The function (KPI delivery), not the seat.
A KPI structure defined during scoping and contracting.
Pods are designed to run against KPIs agreed during scoping and reviewed together on the cadence set in your agreement. Commercial remedies, if any, are defined in that agreement. We are operators, not seat-vendors; the math has to work or the deal doesn't.
What is a Nearshore AI Pod?
A function-as-a-service: 3 to 8 nearshore operators (Latin America, time-zone-aligned with US business hours) running alongside a tuned AI agent stack, owning one of your operational functions end-to-end, Sales, CS, RevOps, Recruiting, Finance Ops, or Support. One SLA, one bill, one weekly QBR. We staff, train, supervise, and scale it.
How is this different from a BPO or staff-augmentation firm?
BPOs sell seats; we sell outcomes. A traditional BPO bills you per FTE and leaves the AI question to you. We blend human + AI capacity under one SLA, own the workflow design, and ship measurable function-level KPIs (pipeline created, tickets closed, time-to-fill, days-to-close). You buy the function running, not the labor input.
Why nearshore vs offshore?
Time-zone alignment, cultural fluency, and English proficiency materially change response times and customer experience. For functions touching revenue or customers, SDR, CS, RevOps, Support, nearshore Latin America beats offshore on conversion, CSAT, and stand-up speed. We use offshore selectively for back-office work where it earns its place.
How fast is deployment?
About 30 days from signed scope to production for standard scopes, depending on access and complexity. Week 1: process mapping and instrumentation. Week 2: pod assembly and AI agent training on your tools and data. Week 3: supervised dry-run. Week 4: go-live under SLA. We do not run quarter-long pilots.
What does this typically cost?
Flat monthly per pod, scoped to function and volume. Typically lower than building the same capacity in-house once you factor in recruiting, benefits, management overhead, tooling, and ramp time. Exact pricing is built in the assessment.
Who manages the pod day-to-day?
We do. Every pod has a named XCAILE operator (your account lead) plus a delivery lead inside the pod. You get a single point of accountability, weekly QBRs, and a live dashboard of the function's KPIs.
What happens to my existing team?
The pod is designed to slot into your org, not replace it. Most clients use a pod to take repetitive volume and tier-1 work off their team's plate so internal hires focus on strategy, complex deals, or product. We can also absorb a struggling function entirely if that's the goal.
Can we start small and expand?
Yes. The standard entry is one function. Once we prove the unit economics, usually inside 60 days, you can add a second pod, expand pod size, or layer in compliance and global employment to take the function international.
What about data security and compliance?
Documented security and access controls, signed DPAs, least-privilege access via your IdP, country-of-origin transparency on every operator. For regulated functions (Finance, Healthcare, Legal), we tailor controls and tooling to your regime.
Talk to us about a Nearshore AI Pod.
Team leads, function heads, and COOs, we'll design a 30-day pod for one workflow.
Scope your pod in one working session.
One 60-minute session. We map the function, the KPIs, and the unit economics, then hand you the pod design and the number. You decide from there.
60-minute working session · No obligation · NDA on request