For AI Labs and AI-Native Companies · Seed to Series C

Keep your AI company's sales and customer work moving.

Build the sales and customer-delivery capacity behind your AI product. Scope founder-led sales support, SDRs, technical sales, implementation, onboarding and customer success around your product, customers and growth plan.

Need expert reviewers or model evaluation? Scope my evaluation team.

See the work

A role, a complete team or a growth program. Share the team or function you need, target customers and timing. We reply with the proposed role mix, responsibilities, required inputs and commercial next steps.

Support the sales conversations already happening.Account briefs, meeting prep, reviewed follow-ups, CRM discipline.Build capacity behind customer delivery.Onboarding, implementation coordination, issue ownership, adoption.

AI-fluent operators

Timing set in writing

Pods that scale weekly

Product capability validated

Weekly product enablement

Time-zone aligned in LatAm

Scales pod by pod

The AI-company problem

Sales follow-up and customer onboarding need people who can keep up.

Generic SDRs don't work

Your customer is technical. A junior outbound rep reading a generic script gets ignored or, worse, embarrasses the brand.

Founder-led is the ceiling

Founders are the best sellers, and the worst use of time on demo logistics, follow-ups, and CRM. That is not where their time should go.

CS can't keep up with the roadmap

Every release expands the surface area. Without a team that re-enables weekly, support quality collapses and NRR with it.

The mechanism

AI-fluent humans + your product + our agent stack. Shipped as a pod.

We recruit and validate people against your product, customer and role requirements, then employ, pay and manage the agreed team. Product specialists, technical sales and customer-success roles are matched to the work, with approved AI tools supporting research, drafting and account operations inside your stack.

The capability brief

We define the product, domain and customer-work capability required, then source and validate fit. Availability is confirmed during scoping.

The stack

AI agents for research, sequencing, technical drafting, post-call summaries, CRM ops. Your tools, your data, your prompts.

The cadence

Weekly product sync, mid-week re-enablement, Friday-locked playbooks. Roadmap-paced sales and CS, not quarterly retraining.

Pods for AI-native motion

Six pod types, designed for AI labs.

Founder-Led Sales Support

Research, multi-thread sequencing, demo prep, post-call follow-ups, CRM hygiene, expansion mapping. Founder keeps the room; pod runs the motion.

AI-Native SDR Pod

Technical outbound to AI-savvy customers. Account-tiered, signal-based, human-voiced + AI-volume. KPI: qualified meetings with the right prospects.

Technical Sales / Solutions

Pre-sales architecture, eval design support, POC coordination, security questionnaires, technical proposals.

AI Customer Success

Adoption playbooks for AI products, value reviews, expansion mapping, model/version migration support, advocacy.

AI Onboarding and Implementation

White-glove activation, integration scoping, success-criteria contracting, time-to-first-value compression.

Community / DevRel Ops

Discord/Slack moderation, content amplification, dev sentiment tracking, contributor pipelines, event ops.

Which roles does your customer work need?

Sales support and SDR: Research, outreach, follow-through and pipeline operations. You retain targeting and commercial approvals.
Technical sales and solutions: Product demonstrations, solution discovery and technical sales support, with role-specific capability validated.
Implementation: Technical delivery and integration only where expressly scoped and capability validated. Coordination alone is not production engineering.
Onboarding and customer success: Customer launch, adoption and account operations. Your team retains product commitments and commercial approvals.
Human evaluation: A separate calibrated review and quality scope. See human AI evaluation.

Forward-deployed engineering and GTM engineering require their own technical scope and validated capability. They are not interchangeable with technical sales, implementation coordination or customer success.

Illustrative example · Two workflows

The work you can inspect, before you buy it.

Standard scope shown for illustration. Not a measured customer result. Prospecting and SDR pods remain available and are scoped separately.

Sales workflow

Support the sales conversations already happening.

Founder-Led Sales Support pod

Input: Your calendar, CRM access, the accounts in play and notes from past calls.
Role responsibilities: Account brief before each meeting, meeting preparation, follow-up drafted the same day, CRM next step logged, weekly action review.
AI assistance: Account research, call summaries, first drafts of follow-ups and CRM field updates.
Human review: The operator checks every brief and draft for accuracy and tone. Nothing is sent without the approval you define.
Finished artifact: A one-page account brief, an approved follow-up, a dated CRM next step and a Friday action review.
Your contribution: You keep the conversation, approve outbound messages and confirm priorities each week.

Illustrative finished artifact · Account brief and approved follow-up

Account: Northstar AI · Buyer: VP Customer Operations · Meeting: Thursday, 14:00
Decision needed: confirm the onboarding owner and agree the first-live-workflow milestone
Approved follow-up: owners named, next meeting proposed, CRM action due Friday

Fictional example for scope illustration, not a customer result.

How your first scope is defined

Work included: The workflow above you want handled first, written as tasks and outputs.
Coverage and volume: Hours, time zones and the assumed number of accounts, meetings or onboardings per week.
Tools: The CRM, helpdesk, docs and AI tools the team works inside. Your stack, your data.
Dependencies: Access, approvals and the people on your side the team relies on.
Measures: What gets reviewed weekly, for example follow-ups sent on time, CRM completeness, time to first successful use.

Timing and pricing depend on the workflow, volume, access, approvals and team shape. Both are confirmed in your written proposal.

Your deploy plan

A clear path from product knowledge to supervised customer work.

Days 1 to 3
Step 1
Product deep dive
Engineering and founder sit with the pod lead and the team is selected.
Days 3 to 7
Step 2
Working under review
First team members work under review while access, tooling and playbooks are confirmed.
Day 14
Step 3
Full team running your playbook
Sales follow-through, SDR and onboarding coordination run at full capacity. Technical sales, implementation and customer success reach full capacity by day 21.
Every week
Step 4
Product updates trained in
New releases are trained into the team so the pitch and the playbook stay current.

First team members working in 3 to 7 days. Full team running your playbook in 14 days for sales follow-through, SDR and onboarding coordination, or 21 days for technical sales, implementation and customer success, once scope, access and product training are confirmed.

Onboarding and customer success

Give every new customer a team that can get them live.

Scope implementation and customer-success capacity around your product, your customers and the work waiting to be done.

The proposed work

New customer onboarding, from kickoff to first successful use
Implementation and configuration inside your product
Technical questions answered during ramp, with your engineers protected
Adoption follow through, health checks and renewal preparation

Responsibilities and cadence

Named owner per account, with a documented onboarding routine
Weekly product enablement so the team stays current with your releases
Mid-week re-enablement on anything that shipped, playbooks locked Friday
Escalation path to your team for product defects and to your XCAILE operator for quality and cover

Acceptance and your inputs

Acceptance criteria agreed in the scope, for example time to first successful use and onboarding completion
We need product access, documentation and a technical contact for enablement
Your definition of a live customer, and the systems the team works in
Setup timing is confirmed from the product, access, approval and team requirements

Existing XCAILE implementation and customer-success capability, scoped to your product. Send it in writing, a call is optional.

How we compare

Why AI labs pick us over the obvious alternatives.

	XCAILE	Your own US hire	An outsourced SDR program	AI tools only
Who owns the work	Your named XCAILE team, reviewed weekly	You, once hired	The program's account team	No one, you run the tool
How the team starts	Role-specific milestones, with scope and training confirmed	Your recruiting and onboarding process	Confirm the provider’s role scope and onboarding	No team: your staff still does the work
Product training	Included in the agreed team routine	You design and run it	Confirm what the program includes	Your team owns enablement
Management	XCAILE manages the agreed team	Your managers own it	Confirm the program’s responsibilities	Your managers run the work

Ready when you are

If you are shipping faster than you can staff the GTM motion behind it, start here.

Direct written reply, clear scope, commercial next steps

What changes

The founder writes code again. The motion ships every week.

Written

Start timing confirmed for the selected workflow

Founder hours

Designed to return selling and support hours to product

Weekly

Product to pitch to playbook enablement cadence

At a glance

Product: AI-fluent GTM, sales, and CS pods built for AI-native companies.
Buyer: AI labs, foundation-model companies, AI-native SaaS, applied-AI startups (seed to series C).
Deployment time: Confirmed in writing from the selected workflow, access, approvals and team fit.
Pod types: Founder-Led Sales Support, AI-Native SDR, Technical Sales / Solutions, AI Customer Success, AI Onboarding, Community / DevRel ops.
Operator profile: Capability requirements are defined by scope; relevant experience and actual availability are validated before a team is proposed.
AI stack pairing: Operators paired with the XCAILE AI agent stack for research, sequencing, technical drafting, CRM ops.
Enablement cadence: Weekly product sync, mid-week re-enablement, Friday-locked playbooks, roadmap-paced.
Geography: Nearshore Latin America, time-zone aligned with North American hours.
Pricing model: Flat monthly per pod, materially below US in-house build.
Founder fit: Designed to support, not replace, founder-led sales, founder keeps the room, pod runs the motion.

Delivery commitment

A full team running your playbook in 14 days.

What AI founders ask

Why do AI-native companies need a different workforce model?

Because your customer's journey, product cycle, and unit economics are different. Your customers don't want to talk to traditional SDRs; your CS team has to explain capabilities that didn't exist six months ago; your roadmap moves weekly. A general staffing or BPO playbook breaks against AI-native motion. We build GTM and CS teams that ship at AI-company speed and speak the product fluently.

What does the XCAILE AI GTM team actually look like?

A blended squad: nearshore humans who are AI-fluent (former AI ops, ML PMs, technical CSMs, AI-literate SDRs) paired with our AI agent stack for research, sequencing, technical answers, and CRM hygiene. Pods cover Founder-Led Sales support, AI-native SDR, Technical Sales / Solutions, AI Customer Success, AI Onboarding, and Community / DevRel ops.

How fast can we deploy?

Are your operators technical enough for an AI product?

Each scope defines the required product and domain fluency. XCAILE sources and validates relevant capability, then confirms actual availability and fit before proposing a team. We do not represent illustrative profiles as available candidates.

We already use Clay, Apollo, Gong, and 8 other tools. How does this fit?

We meet your stack. The pod runs inside your tools and our team uses approved AI tools inside your stack. Most AI companies discover the bottleneck is not 'more tools' but the human capacity and operating cadence to actually use what they have. We bring both.

Can you handle Founder-Led Sales without taking it from the founder?

That's the design. Founder-led pods absorb everything except the conversation that has to be the founder: research, sequencing, follow-ups, demo logistics, CRM, post-call summaries, multi-thread account expansion. The founder keeps the room, we run the motion behind it.

How do you handle the speed of our roadmap?

Product enablement is built into the team. Your release notes and approved documentation inform the sales and customer playbooks, with human review of technical answers before use. We agree the update routine and approvals with your product team.

What does this cost?

Commercials are scope-defined and may be role-based, pod-based, or milestone-based depending on the work. The proposal states responsibilities, capacity assumptions, dependencies, timing, and fees before work starts.

For AI Labs & AI-native companies

Scope your GTM and customer team.

Send the sales follow-through, onboarding, implementation, or customer-success work that needs an accountable owner.

Keep engineering on the roadmap.

Send a role, a complete sales and customer team, or a growth program. We reply with the role mix, responsibilities, product inputs and commercial next steps. No call needed.

Founder-friendly, scoped around your product and motion

Not the right fit?