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01 / 06 · AI INTEGRATION

We integrate Claude API into enterprise systems. Without replacing what you already have.

Approach API-first: agents, copilots, RAG, workflow automation. Implementation with compliance (LFPDPPP, SOC 2 alignment), observability of LLM costs and handoff with team training.

01 · WHAT WE INTEGRATE

Models we work with.

PRIMARY

Claude (Anthropic)

Our recommended model for most enterprise use cases. Best for long-context reasoning and instruction-following.

WHEN APPLICABLE

OpenAI GPT-4 / 5

When the use case requires GPT specifics: vision pipelines, real-time API, specific function calling patterns.

SPECIFIC CASES

Gemini (Google)

For projects with Google Workspace integration, multimodal at scale, or when client mandates Google.

DATA SOVEREIGNTY

Open-source (Llama, Mistral)

When there are data residency constraints or the client requires running models on their own infrastructure.

02 · COMMON USE CASES

Where we usually deploy AI.

  • AI agents for customer support
  • Internal copilots for commercial teams
  • RAG over internal documentation
  • Workflow automation
  • Legal / technical document analysis
  • Assisted proposal generation (ref: GV Proposals)
03 · REFERENCE IMPLEMENTATION

GV Proposals: 2 years operating on Claude API.

Internal product we use daily to generate commercial proposals. Lives in production since 2024 with measured impact: ~80% reduction in proposal-writing time, higher acceptance rate, and a documented stack we use as blueprint for client AI projects.

Next.jsPayload CMSClaude APIPostgreSQLVercel
04 · COMPLIANCE & SECURITY

What we guarantee.

  • LFPDPPP compliance (Mexican enterprise) operating under signed NDA from first contact.
  • SOC 2 alignment for US enterprise — technical & procedural controls aligned to the framework.
  • Client data NEVER used for model training (Anthropic API, OpenAI Enterprise, Gemini).
  • LLM cost auditing — token usage, latency p95/p99, retry rates instrumented from day 1.
  • Call and latency observability via OpenTelemetry / Datadog / client-preferred APM.
05 · PROCESS

4 phases, end-to-end.

01 · AUDIT

1-2 weeks

Identify AI use cases with clear ROI in your current systems.

02 · DESIGN

1 week

Integration architecture + prompt engineering + cost modeling.

03 · BUILD

3-6 weeks

Implementation + testing + observability + security hardening.

04 · OPERATE

Continuous

Monitoring, cost optimization, fine-tuning, model upgrades.

Have an AI use case in mind?

30-min discovery call. We map opportunities and quantify potential ROI before any commitment.

Schedule discovery →