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Packaged solutions

Your business processes automated by a tested AI agent

Skills, hooks and MCP packaged using the agentic architect methodology. Your teams use AI as a reliable business tool.

The problem

Why ad hoc LLM use does not hold up in production

Business guardrails missing

Models respond outside the agreed scope, without validation or an audit trail. The result is inconsistent answers, declining quality and legal exposure.

System access missing

Without connections to your systems, AI has no access to your CRM, databases or internal tools. Your teams copy and paste. The model lacks the context.

Tests missing

No guarantee that a model update or prompt change will not break today’s workflow. Regressions are discovered in production.

Method missing

Impossible to maintain, hand over or develop further. The project lives or dies with the person who coded it, and skills transfer becomes impossible.

The answer

What a Colombani.ai agent contains

01

Skills

Business expertise encoded as reusable modules that can be versioned: sales processes, accounting standards, clinical protocols, legal rules.

02

Hooks

Business rules applied automatically at each step: input validation, structured logging, guardrails, audit traceability.

03

MCP

Controlled access to internal systems (CRM, ERP, document repository, business APIs) without exposing credentials to the user or the model.

04

Anthropic templates

Compliance with official best practices: prompt structure, tool use, agent loops, context management.

05

Tests + benchmarks

Reproducible evaluation suite. Comparison against a baseline (a human process or a competing tool). Metrics: accuracy, latency, cost.

06

Docs + monitoring

Technical documentation for your teams. Usage dashboards. Regression alerts. You can detect drift before it becomes visible.

Methodology

Agentic Architect in 5 phases

1. Architecture

Workflow mapping with the business team. Decision points and success metrics identified. Deliverable: functional specification + KPIs.

2. Design

Selection of required skills, hooks and MCP. Choice of suitable Anthropic templates. Effort and risk estimation. Deliverable: technical design.

3. Build

Continuously tested code. Strict compliance with Anthropic templates. Code review at every step. Deliverable: working plugin + test suite.

4. Benchmark

Evaluation on real cases against a baseline (a human process or an existing tool). Metrics: accuracy, time, cost. Iteration until the defined quality threshold is reached. Deliverable: a benchmark report.

5. Deployment

Pilot rollout to one team. User training. Monitoring set up. Deliverable: plugin in production + documentation + 30 days of support.

Use cases

Example plugins already designed using this methodology

Sales Ops Plugin

Inbound lead qualification: email reading, scoring, a sales briefing before the meeting, CRM updates. Stack: CRM-aware skills + validation hooks + HubSpot or Salesforce MCP.

Legal Review Plugin

Contract document analysis: extraction of sensitive clauses, GDPR and AI Act checks, a risk report. Stack: legal skills + source citation hooks + document repository MCP.

Month-end Close Plugin

Month-end reconciliation: multi-source aggregation, anomaly detection, report generation. Stack: accounting standards skills + control hooks + ERP MCP.

Medical Coding Plugin

ICD-10 code generation from clinical notes: extraction, suggestion, validation. Stack: medical nomenclature skills + traceability hooks + EHR MCP.

Why this approach

Six guarantees that make the difference

CCA Foundations from Anthropic

Methodology built on the Claude Certified Architect certification and the best practices published by Anthropic.

Qualiopi

Quality framework applied to engineering processes. Traceable deliverables, decisions and evaluations.

Tests + benchmarks

Every plugin ships with its evaluation suite. The result is reproducible on every run, and quality is measured.

Source code delivered

Code, configurations, documentation and the repository belong to you, with no subscription or recurring licence fees for the plugin.

Monitoring included

Usage dashboards and regression alerts. You know if the plugin drifts before users report it.

Optional maintenance

Monthly subscription for enhancements and monitoring Anthropic model updates. You retain control of the schedule, with continued support after delivery.

Certificates, insurance and how indicators are calculated

Frequently asked questions

How does this differ from conventional AI development? +

A conventional AI development project delivers a script or an API. A Colombani.ai plugin delivers a structured system (skills + hooks + MCP), tested, documented and aligned with Anthropic templates, with its evaluation suite and monitoring. A script stops working at the first model update. A plugin evolves.

How long until a plugin is operational? +

From 4 to 12 weeks, depending on workflow complexity and the number of systems to integrate. A simple use case (lead qualification) can be in production in 4 weeks. A plugin spanning multiple systems with complex integrations takes 8 to 12 weeks.

Which systems can be integrated through MCP? +

Any system with an API (REST, GraphQL, SOAP). Connectors available for Salesforce, HubSpot, Notion, Google Workspace, Microsoft 365, GitHub, Slack and SQL or NoSQL databases. Custom connectors possible for internal systems.

What happens when Claude evolves? +

The plugin is versioned. Every Anthropic model update is tested against the evaluation suite before it is deployed. If you subscribe to maintenance, Colombani.ai monitors model updates and handles migrations. Otherwise, the documentation explains how to do this in-house.

Can we use a local model for sensitive data? +

Yes. Plugins are compatible with Claude (cloud) and with local models (Mistral, Qwen via Ollama). The choice is made during scoping, based on data sensitivity. See the sovereign AI consulting offer for architectures that run entirely locally.

How do you ensure the plugin stays reliable over time? +

A test suite runs on every change. Monitoring raises an alert when usage or quality drifts. Documentation lets your team maintain the plugin without depending on Colombani.ai.

Got a project in mind?

Describe your situation. The first 30-minute call is free. Get a frank response within 48 hours.