Prompt Engineering & Fine-tuning
Systematic prompt engineering and model fine-tuning for production AI. Reduce costs, improve accuracy, maintain brand consistency.
What is Prompt Engineering & Fine-tuning?
Good prompt engineering is the difference between an AI demo and an AI product. We take a systematic, measurable approach — not trial-and-error. Every prompt is versioned, tested against evaluation datasets and optimized for both quality and cost.
When prompts alone aren’t enough, we fine-tune models on your specific data. We handle dataset preparation, training runs, evaluation and deployment — with clear metrics showing the improvement over base models.
Our team has optimized prompts and fine-tuned models for content generation, classification, extraction and conversational AI across multiple industries.
Why build with us
Systematic Process
No trial-and-error. We use structured prompt patterns, evaluation datasets and measurement frameworks to optimize systematically.
Version Control
Every prompt version is tracked, tested and measured. Rollback to any previous version with confidence.
Cost Optimization
Shorter, more effective prompts that produce better results at lower token cost. We typically reduce prompt costs by 40%.
Fine-tuning Expertise
When prompts aren't enough, we fine-tune models on your data with proper dataset preparation and evaluation.
What we build with Prompt Engineering & Fine-tuning
Prompt Registry
Version-controlled prompt library with testing, A/B deployment and rollback capabilities.
Evaluation Pipeline
Automated testing against golden datasets with accuracy, consistency and cost metrics.
Fine-tuning
Dataset preparation, training runs and evaluation for GPT-4o-mini, Llama 3 and Mistral models.
Optimization
Iterative prompt refinement with measurable improvements tracked across every version.
How we deliver
Audit
Week 1Review existing prompts, identify weaknesses and build evaluation datasets.
Optimize
Week 2-3Systematic prompt iteration with automated evaluation on every change.
Test
Week 3-4A/B testing in production with statistical significance measurement.
Deploy
Week 4Production deployment with monitoring and rollback capabilities.
How you can work with us
Fixed-Price Project
Defined scope, fixed timeline, guaranteed deliverables. Best for MVPs and well-scoped features.
- Full scope defined upfront
- Milestone-based payments
- 8-16 week delivery
- 30-day warranty
Dedicated Developer
A senior developer assigned to your team full-time. Minimum 1 month engagement.
- 160 hours/month
- Daily standups
- Weekly demos
- Flexible scaling
Team Augmentation
A full team of developers, designers and architects embedded in your organization.
- Cross-functional team
- Quarterly engagement
- Dedicated PM
- Architecture oversight
Our Prompt Engineering & Fine-tuning technology stack
Models
Framework
Evaluation
Frequently asked questions
Start with prompt engineering — it’s faster, cheaper and easier to iterate. Move to fine-tuning when you need consistent brand voice, domain-specific accuracy above 95%, or 10x cost reduction at scale.
OpenAI GPT-4o-mini and GPT-4o, Anthropic Claude (via AWS Bedrock), Llama 3, Mistral and other open-weight models. We help you choose based on your accuracy, cost and data privacy requirements.
We use a prompt registry with version control, automated evaluation against golden datasets, A/B testing in production and rollback capabilities. Every change is tracked and measured.
Typically 2-4 weeks: Week 1 is understanding your task and building eval datasets. Week 2-3 is systematic prompt iteration. Week 4 is production deployment with monitoring. You own all prompts and evaluations.