Variation generation for performance
Pipeline producing 80 copy + creative variations per sprint, all within brand voice. Growth team is no longer the creative bottleneck and became a test curator.
Personalization that's real, at industrial scale.
For growth and sales teams that want AI without becoming a marketing parody. Always with brand voice and privacy respected.
What we do
Marketing that grows — without losing identity.
The AI layer that respects what makes your brand itself.
Content with guardrails
Copy, creative and variation generation at scale — with brand voice, compliance and review loops.
Predictive qualification
Propensity and fit models to prioritize SDRs and likely closes.
1:1 personalization
Messages, offers and journeys adapted at runtime, with privacy preserved.
AI-powered attribution
Media mix and multi-touch attribution models — invest where it actually performs.
Positioning
Real personalization isn't a trick. It's infrastructure.
AI-personalized brand isn't swapping the first name in the email. It's a system that respects voice, privacy, journey and context — scaling what the creative team decides, without becoming growth theater. Done right, no one notices the AI behind it.
By the numbers
What creative scale delivers after the brand audit.
0×assets produced per sprint
+0%lift in qualification conversion
−0%copy production time at scale
0%of assets pass through the brand guardrail
How we build
From brand book to scale variation.
Every piece coming out of the system passes through guardrails that codify what makes the brand itself. The creative team audits samples, not every piece.
- M1
Brand audit
We codify voice, tone, vocabulary and do/don't from brand book + winning examples.
Output Versioned brand spec.
- M2
Creative pipeline
Copy + creative + variation generation with guardrails applied before human review.
Output 80+ assets per sprint, all brand-safe.
- M3
Personalization
Messages, offers and journeys adapted at runtime considering stage and documented privacy.
Output 1:1 segmentation without opt-out violation.
- M4
Attribution
Media mix + multi-touch fed by real data. ROI by channel, creative and segment.
Output Investment decision in <24h.
Under the hood
The set that delivers creative + data.
Generation
- Claude (long-context)Default for voice-aware copy.
- Midjourney / Imagen 4 / FluxVisual + variations.
- Veo 3 / Runway / KlingShort-to-mid form, cinematic quality.
Brand guardrails
- Custom semantic evalsVoice + do/don't.
- Style classifierTrained on brand sample.
- Compliance checkLGPD + regulated sector.
Activation
- HubSpot, SalesforceNative CRM.
- Klaviyo, Customer.ioLifecycle.
- GA4 + MixpanelMeasurement.
In production
AI marketing without losing voice.
B2B predictive lead scoring
Propensity model trained on historical CRM. Reduced SDR time on cold leads and lifted close rate because the team focuses on who's actually ready to buy.
Email journey personalization
Each email generated at runtime considering lead stage, recent behavior and privacy rules. No artificial opt-out, respecting documented preferences.
Frequently asked
About AI for marketing.
How do you prevent AI from producing generic copy?
We build a brand-guardrail system fed by the brand book + examples of what worked and didn't. Every output goes through semantic and stylistic checks before reaching human review.
What about customer data privacy?
All PII is redacted before any model call, and the system respects documented opt-outs in the CRM. For sensitive cases we use a self-hosted model — no data leaving the customer's cloud.
Does attribution work on long journeys?
Multi-touch attribution models work when journey data is captured consistently. The first step is usually fixing event capture before modeling attribution.
Do you replace marketing agencies?
No. LA AI is the AI layer that amplifies whoever is doing the creative work. We work alongside in-house or external agencies.