Model Selection & Fine-Tuning
We benchmark open and frontier models, then fine-tune or align them to your domain, tone, and accuracy targets.
← All servicesGenerative AI
Turn large language models into revenue-generating products
We design, fine-tune, and deploy LLM applications that reason over your data and ship value — not demos.
- Draft, summarize, and personalize marketing content at scale
- Generate and review code inside developer workflows
- Automate contract and document drafting for legal teams
- Power natural-language product search and recommendations
40%avg. cost cut vs. off-the-shelf LLM usage
Capabilities
Model Selection & Fine-Tuning
Prompt & Context Engineering
Guardrails & Safety
Evaluation Harnesses
What Generative AI delivers
Production-grade generative ai, engineered and shipped by one accountable team.
Prompt & Context Engineering
Structured prompting, few-shot patterns, and dynamic context assembly that squeeze maximum quality from every token.
Guardrails & Safety
Content filtering, jailbreak defense, PII redaction, and policy enforcement to keep outputs safe and on-brand.
Evaluation Harnesses
Automated eval suites with golden datasets and LLM-as-judge scoring so quality never regresses in production.
Structured Generation
Reliable JSON, function calls, and schema-constrained outputs that plug directly into your existing systems.
Streaming & Latency Tuning
Token streaming, caching, and speculative decoding that keep responses fast and infra bills low.
From idea to production
A transparent, low-risk path — validated on your data before you commit.
Discovery & Feasibility
We map your use case, data, and constraints, then prove feasibility with a scoped proof of concept.
Model & Data Strategy
We choose the right base model, curate training and eval data, and define measurable success criteria.
Build & Fine-Tune
We engineer prompts, fine-tune where it pays off, and wrap everything in robust guardrails and evals.
Deploy & Optimize
We ship to production with monitoring, then continuously tune cost, latency, and quality against live traffic.
Where teams put it to work
- Draft, summarize, and personalize marketing content at scale
- Generate and review code inside developer workflows
- Automate contract and document drafting for legal teams
- Power natural-language product search and recommendations
Outcomes teams actually see
3xfaster content and code generation
40%lower inference cost per request
95%+output accuracy on domain tasks
–60%manual review effort
Questions, answered
We start with prompting and retrieval because they are cheaper and faster to iterate. We fine-tune only when data shows it meaningfully improves accuracy, cost, or latency.
Yes. We support self-hosted open models and private cloud deployments so your data never leaves your boundary, with full audit logging.
We ground models with retrieval, constrain outputs to schemas, and run continuous evals with human-in-the-loop checks on high-risk paths.
We are model-agnostic and benchmark frontier and open-weight models per use case, then choose the best balance of quality, cost, and control.
◆ Let's build
Ready to put AI to work in your industry?
Tell us your challenge. We'll come back with a concrete, no-obligation plan and a live demo of what's possible for your team.
- Free AI auditWe map the highest-ROI AI opportunities across your workflows.
- Prototype in weeksA working proof-of-concept on your real data before you commit.
- One accountable teamStrategy, models, data and deployment — end to end.
120+ teams shipped across 6 industries
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