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01 / 06 · AI INTEGRATION

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

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

01 · WHAT WE INTEGRATE

Models we work with.

PRIMARY

Claude (Anthropic)

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

WHEN APPLICABLE

OpenAI GPT-4 / 5

When your 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 the client mandates Google.

DATA SOVEREIGNTY

Open-source (Llama, Mistral)

When data residency constraints exist or the client needs to run models on their own infrastructure.

02 · COMMON USE CASES

Where we usually deploy AI.

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

GV Proposals: 2 years running on Claude API.

Internal product we use daily to generate commercial proposals. Live in production since 2024 with measured impact: ~80% reduction in drafting time, higher acceptance rates, and a documented stack we use as blueprint for AI projects with clients.

Next.jsPayload CMSClaude APIPostgreSQLVercel
04 · COMPLIANCE AND SECURITY

What we guarantee.

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

Ongoing

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

Do you have an AI use case in mind?

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

→ Schedule discovery