Custom-Tuned AI for Marketing That Understands
Your Brand
Accelerate campaign execution, boost content precision, and ensure brand-safe AI outputs with fine-tuned large language models built for your marketing stack.
LLM Fine-tuning can be a complex undertaking. Before committing resources for a full-fledged pilot, get deep-down feasibility assessment including pros and cons of using alternative approaches like prompt engineering or using internal models of your mar-tech vendors.
Problems We Address
Manual content creation is slow, costly and completely lacks any personalization or context
Generic AI outputs lack brand/context awareness
Manual prompting is simply too cumbersome and does not scale
Lack of understanding of governance and compliance risks with out-of-the-box LLMs or native vendor solutions
Ad-hoc execution. No strategic application or data roadmap that can cater to ALL our use cases
Need a deeper, techno-commercial understanding of resources, tools required and cost projections
How we do it
A methodical, framework-driven approach to developing LLM fine-tuning blueprints for marketing

Use Case Discovery using a structured approach
Use Case Discovery
Identify the right candidates for fine-tuning vs. prompt engineering. Our process prioritizes feasibility, ROI, and speed-to-value.
Comprehensive Data Preparation Framework for LLM tuning
Data Preparation
Transform raw marketing data into structured, high-quality training sets. We ensure consistency, relevance, and compliance throughout.
Select the best model for your use case.
Model Selection & Evaluation
Choose the most suitable LLM for your marketing needs. We evaluate open-source, commercial, and custom models for cost, performance, and fit.
Model training using the most effective approach
Model Training
Fine-tune models on your domain-specific marketing data. Our approach captures brand voice, customer context, and campaign intent.
Evaluation using AI-generated predictor models
Model Evaluation
Measure model performance using business-aligned metrics. We benchmark outputs against marketing KPIs like engagement and conversions.
Model deployment and integration
Model Deployment & Integration
Integrate the fine-tuned model into your Martech stack. We ensure scalable, secure, and API-ready deployment for real-world use.
Robust MLflow Integration
Expert consulting on using MLflow to track experiments, compare model versions, and manage deployments. Integrated with platforms like Databricks, AWS, and Kubernetes, it ensures transparency, reproducibility, and smooth handoffs from training to production.

Real-World Use Cases That Drive Marketing ROI with AI
From hyper-personalized emails to global campaign localization, see how fine-tuned LLMs deliver scalable, brand-safe automation for modern enterprise marketing teams.
Email personalization at scale
Generate hyper-personalized email copy tailored to audience segments, buyer personas, or real-time behavior.
SEO-optimized content creation
Produce blog posts, landing pages, and metadata that align with high-intent keywords while maintaining brand voice.
Localized campaign generation
Automatically generate campaign assets—emails, ads, landing pages—in multiple languages and regions, fine-tuned for cultural nuance, tone, and compliance.
Internal knowledge assistants for marketers
Deploy AI copilots trained on internal documents, campaign playbooks, and guidelines to support marketers with fast answers, content templates, and regulatory references.
Social media automation
Create timely, platform-optimized social posts (tweets, captions, CTAs) that align with your campaigns and voice.
Product descriptions tuned for brand voice
Auto-generate product descriptions that reflect your brand’s unique tone—whether it’s luxury, playful, or technical—across thousands of SKUs.