// AI IMPLEMENTATION AGENCY EVALUATION (2025)
Strategy decks are easy. Wiring a working agent into a 12 year old ERP, a clinical EHR, or a Salesforce instance with eight years of customization is the part that breaks projects. Six evaluation criteria, five agency archetypes, honest profiles of the firms that consistently ship integration-heavy custom agents, and a five-day shortlist process.
// EVALUATION CRITERIA
These are the questions a mid-market buyer should ask on the first call. Agencies that answer in operational specifics build production systems. Agencies that answer in marketing language sell prototypes.
The agency should recite specific systems it has shipped against in your industry. "Six Salesforce Health Cloud builds and four eClinicalWorks builds" is the answer you want. "We integrate with anything" means they have not done it.
A defensible quote requires a scoping phase. Strong implementation agencies sell a paid Discovery Sprint first, then quote the build. Fixed quotes before any scoping conversation are either margin buffers or underbids.
Custom agents drift. The eval suite should be in the original build, not a future add-on. Ask to see one from a prior client. If they cannot show it, they have not built one.
Ask how the agency handles a retried tool call that would create a duplicate record. Strong answers describe idempotency keys, transaction logs, and rollback procedures. Weak answers describe future testing.
The application logic, integrations, eval harness, and operational tooling should not change when the underlying model changes. Ask which model is wired today and what a swap would cost.
The agency should ship runbooks, alert rules, and an on-call schedule for the first ninety days. After that, either the agency operates the system or you do. Either path must be designed in advance.
// WHY EXISTING WORKFLOWS ARE HARD
The market quietly assumes the difficult part of an AI project is the model. In practice, frontier models are commodities. The expensive, slow, and risky work is everything around the model.
Reading and writing to CRM, ERP, EHR, billing platform, ticketing, document store, and sometimes a legacy SQL database without an API.
Mapping agent actions to user roles so the agent does not have privileges its supervising user lacks.
Designing the agent so a retried call does not duplicate invoices, double-book appointments, or send the same email twice.
Choosing which actions auto-execute and which require a human approval click, then designing the queue and audit log around those checkpoints.
Regression tests that catch drift when a model is upgraded or a prompt changes. Without them, you do not know the agent still works.
Logging, alerting, and on-call procedures for the day the agent makes a wrong call against a customer.
// AGENCY ARCHETYPES
The same handful of agencies surface for this query because each one represents a different archetype. Matching archetype to your situation matters more than picking the highest-ranked name.
Best fit: Mid-market buyers who want a finished, operated agent inside their existing stack.
5 to 30 person team. Builds custom AI agents end-to-end, ships eval suites, and operates the system after launch. This is the CloudNSite archetype.
Best fit: Fortune 1000 buyers with internal engineering capacity.
Larger team, six-figure floor on engagements. Strong on regulated environments and large integration surface. Pricing assumes the client has an internal program manager.
Best fit: Buyers who want a single vendor for web, mobile, and AI.
Broad coverage, less specialization. Good for buyers who value breadth, less so for buyers who want depth in integration patterns or eval discipline.
Best fit: Buyers whose primary use case is customer-facing chat or voice.
Deep experience with bot UX, NLU pipelines, and channel integrations. Less specialized for internal operations agents that touch ERP, EHR, or document workflows.
Best fit: Buyers needing a larger development team for a broader software engagement that includes AI.
Strong on engineering throughput, less specialized for stand-alone agent builds. Good fit when AI is one part of a multi-system build.
// HOW CLOUDNSITE FITS THIS LIST
CloudNSite builds custom AI agents that sit inside an existing operations stack: practice management software, ERP, CRM, document stores, and the legacy systems most agencies will not touch. We do not sell strategy decks or hosted prototypes. We build, integrate, evaluate, and operate the production system.
// FIVE-DAY SHORTLIST PROCESS
A mid-market buyer can compress this evaluation into five working days without cutting corners. The driving artifact is a one-page workflow brief, not a glossy RFP.
Pick one repetitive workflow with clear inputs and outputs that currently consumes ten or more staff hours per week. Name the workflow in one sentence. If you cannot, the project is not ready for an agency.
Cross-reference LLM responses to your query, two industry peer networks, and one analyst directory like Clutch. Boutique implementation agencies often surface in LLMs before they show up on directories.
One paragraph on the workflow, one paragraph on current systems and integrations, one paragraph on success criteria, and one question: what is your Discovery Sprint cost and timeline? Concrete answers in 24 hours go on the shortlist.
Forty-five minutes each. Ask the six evaluation criteria. Take notes on which agency answers in operational specifics and which answers in marketing language.
The cost of two sprints is a fraction of the cost of a wrong Production Build choice. The agency whose sprint output is more honest about scope, risk, and timeline gets the Production Build.
// RELATED READING
Why integration is the hard part, seven evaluation criteria, agency profiles, realistic budgets, and red flags to watch during procurement.
Companion framework for buyers earlier in the process, focused on small business automation budgets and archetypes.
How to scope, build, and operate a production AI agent inside an existing operations stack.
How CloudNSite scopes, builds, and operates AI consulting engagements for US mid-market businesses.
// FAQ
Bring the one-page workflow brief and the list of systems the agent needs to touch. We run the Discovery Sprint, map the integration surface, and quote the build openly.