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Agency case study - delivering white-label AI agents to clients with Avery NXR

· Avery NXR

There's a structural opportunity in front of every agency right now that most haven't fully figured out how to capture.

Clients want AI capabilities — agents that handle their operations, scaffold their internal tools, automate their workflows. They don't want to become AI development companies. They don't want to manage cloud LLM contracts. They especially don't want to be the team that figures out how to run AI in regulated or sensitive contexts.

Agencies are the natural intermediary. You already have client relationships. You already understand their workflows. You already deliver implementations. Adding "AI agent development" to your service line is a natural extension if you have the right delivery model.

Most agencies don't yet, because the standard cloud-LLM-based AI tooling creates problems:

The client is on the hook for the cloud LLM subscription (and the renegotiation every year). You're forever tied into their tooling decisions. The data flows through third parties whose contracts the client has to sign. The AI work becomes another vendor relationship the client manages, not an asset they own.

Avery NXR provides a different delivery model. Here's what an agency engagement looks like with it, and what changes about the economics.

The delivery model

You're an agency that engages a client for an AI agent implementation. Standard scope: build 3-5 agents that handle specific operational workflows in their business, integrate with their existing tools, train their team to operate them.

Traditional model (cloud LLM-based):

  • You stand up agents on a cloud agent platform (LangChain hosted, Lyzr, n8n cloud, etc.)
  • You configure their cloud LLM accounts (OpenAI, Anthropic) — they pay the per-call costs
  • You build the workflows; the platform hosts them
  • The client now has a recurring relationship with the platform vendor and the LLM provider
  • When the engagement ends, your client either continues paying or loses the AI capability

Avery NXR model:

  • You install Avery NXR Enterprise on the client's infrastructure (or their cloud, depending on deployment preference)
  • You configure the agents using Avery's visual builder
  • The local SLM handles inference — no per-call costs
  • The client owns the agents; they're configured in software the client now owns
  • When the engagement ends, the client keeps the AI capability — no ongoing dependency on the agency or the platform

The difference matters because it changes what you're delivering. Under the traditional model, you're delivering "agents we built that run on platform X" — the client's ongoing access depends on platform X's continued availability and pricing. Under the Avery model, you're delivering "AI capability your team owns and can extend" — the client's value persists independent of any vendor.

What this enables for the agency

Three things shift in your favor:

You can charge for outcomes, not subscriptions. When the client owns the AI capability, your engagement becomes implementation services — fixed fee or T&M for the build, optional retainer for ongoing extension. Agencies that price on outcomes outperform agencies that price on access.

You can serve regulated clients credibly. Healthcare practices, law firms, financial advisors, government adjacencies — all the clients that have been holding back on AI because of compliance concerns can now be served. The architecture matches their requirements.

You build a repeatable IP base. The agent configurations you build for one client become starting points for the next. The 7 templates that ship with Avery NXR plus the customizations you've developed compound into a delivery library. Each engagement becomes faster.

What changes for the client

Three things matter to them:

Data residency. Their data stays on their infrastructure. The trust conversation gets dramatically easier.

Predictable cost. They're paying for software they own, not subscription that scales with usage. Their AI cost is flat regardless of growth.

Capability ownership. The agents are configured in their software, on their hardware. They own the AI capability the same way they own their database or their CRM data.

For sophisticated clients, this is the differentiator. They've watched their peers get locked into platform vendors. They want to be different.

The economics for the agency

Pricing this engagement model honestly:

Discovery + scoping: $5K-15K depending on complexity Build phase (3-5 agents, basic integrations): $20K-50K Training + handoff: $5K-10K Optional ongoing retainer: $3K-10K/month

For a 10-person agency that delivers 6-12 of these engagements per year, this is $200K-700K in service revenue, on top of whatever else the agency does.

The cost to the agency: Avery NXR Pro licenses for the team ($29/user/month) and Avery NXR Enterprise licenses for client deployments (custom pricing). The platform is not a meaningful cost line item against the engagement revenue.

What the implementation actually looks like

For an agency new to this delivery model, the first engagement typically follows this pattern:

Week 1: Discovery sessions with the client. Identify the 3-5 workflows that matter most. Map out the integration surface (which tools they use, which data sources matter, what triggers each workflow).

Week 2: Install Avery NXR on the client's infrastructure (Enterprise tier, on-prem or their private cloud). Configure the local SLM. Test the foundation.

Week 3-4: Build the agents using Avery's visual builder. Start from the 7 pre-loaded templates where they fit; build custom flows where they don't. Each agent is typically 2-4 hours of build time including testing.

Week 5: Integration. Connect to the client's existing tools via OAuth or API keys. Most common SaaS already supported through the 63 native connectors; custom integrations via HTTP requests for the rest.

Week 6: Training and handoff. Walk the client's team through how to operate the agents, how to extend them, how to add new ones.

Total engagement: 6 weeks for the build, then ongoing as the client wants extensions.

The agency-side advantage that compounds

The thing that becomes obvious after a few engagements: you build a library.

Your version of the Invoice Processor template, customized for fintech clients. Your version of the Resume Screening template, tuned for legal recruiting. Your version of the Daily Sales Digest, set up for B2B SaaS sales models. Each engagement adds to the library.

After 5-10 engagements, you're not starting from scratch. You're starting from a configured starting point that matches the client's industry. Engagements get faster. Margins improve. The agency's IP compounds.

How to start

If you're an agency considering adding AI agent development to your service line, the cheapest test is:

  1. Install Avery NXR Free Desktop tier on your own infrastructure
  2. Build the 7 template agents for your own internal operations (your sales pipeline, your meeting notes, your hiring funnel)
  3. Document the experience as the basis for client conversations
  4. Pitch the first engagement to an existing client you trust

The first engagement teaches you everything you need to know about whether this delivery model fits your agency. Most of the agencies that have tried it report that engagement profitability is higher than their traditional digital service work, because the ownership story commands premium pricing.

Get Avery NXR at avery.software

Enterprise tier with on-prem deployment available for agencies and their clients.