Pure Technology
Generative AI Development

Generative AI products that earn their keep.

Generative AI tools, copilots, and content systems — built for real workflows, with the evals, guardrails, and economics to ship to production.

20+
GenAI products
98.6%
Eval pass rate
60%
Cost vs. naive RAG
Multi-modal
By default

Built for teams that need this to just work.

Who this is for

  • Product teams building AI copilots inside existing SaaS products.
  • Content and marketing orgs scaling output without losing brand voice.
  • Internal tool teams shipping generative workflows for ops, legal, HR.
  • Enterprises needing fully governed GenAI inside their VPC.
Technology Expertise

Technologies Your Teams Already Trust.

We build teams around modern engineering ecosystems ensuring every developer is aligned with your stack, workflows, and delivery standards.

L6

LLM Engineers

Large Language Models

GPT-4oClaude 3.5Gemini 1.5
L6

Fine-tune Engineers

Fine-tuning & Align.

LoRADPORLHF
L5

RAG Engineers

Retrieval-Augmented

LlamaIndexLangChainpgvector
L5

Prompt Engineers

Prompt Engineering

DSPyGuidanceOutlines
What we deliver

A full-stack capability - not a job title.

Every engagement is led by senior practitioners. You meet them in the pitch; they ship the work.

Text generation systems

Copilots, drafting tools, summarizers, and rewriters — tuned to your tone and policies.

Image & vision systems

Generation, editing, OCR, and visual understanding — including diffusion fine-tuning where relevant.

Code generation

Code copilots for internal codebases — fine-tuned on your conventions and architecture.

Multi-modal pipelines

Text + image + audio fused into workflows like document understanding and inspection automation.

Eval & safety

Brand voice evals, factuality evals, bias testing, and red-team coverage tuned per use case.

Cost engineering

Smart routing, prompt caching, model cascading, and per-feature spend budgets.

Outcomes that matter

Numbers from real engagements.

4.7/5
User NPS

Generative drafting tool inside a B2B SaaS — measured at 30-day usage.

60%
Cost reduction

Vs. naive single-model RAG, via smart routing and prompt caching.

11×
Faster workflows

Document review pipeline using multi-modal extraction + LLM summarization.

Related case studies

Proof from similar work.

A few relevant engagements that match this service area.

Global E-Learning & Digital Marketing Agency - QgenX
Digital Marketing, E-Learning & E-Commerce
Case study

Global E-Learning & Digital Marketing Agency - QgenX

Challenge — AI-powered content suite scaled article production from 50 to 200+ monthly with 75% cost reduction.

What we did — Built an AI content that assessment questions, product descriptions, and visual assets. Eliminated freelancer dependency while boosting SEO performance and brand consistency across platforms.

75%
Reduction in content creation time
80%
Improvement in conversion rates
60%
Increase in organic search traffic
Professional Event Photography Organization
Photography, Events & Digital Media
Case study

Professional Event Photography Organization

Challenge — AI facial recognition platform reduced post-production time from 25 to 3 hours while scaling discovery rates from 30% to 94%.

What we did — Built an AI-powered facial recognition platform enabling event guests to instantly retrieve all their photos via selfie upload. Eliminated manual sorting bottlenecks, ensured GDPR compliance, and enabled same-day gallery delivery.

85%
Reduction in post-production time
92%
Increase in client satisfaction
98%
Facial recognition accuracy
Enterprise Software Solutions
Software & IT Services / Customer Success
Case study

Enterprise Software Solutions

Challenge — AI-powered Q&A platform reduced support by 50% while achieving 100% response on documentation.

What we did — Built a scalable AI-driven Q&A web application enabling users to query complex product documentation using natural language. Transformed static manuals into an interactive knowledge experience, significantly reducing manual support & enhancing efficiency.

50%
overhead reduction
100%
Response speed
90%
Data-driven insights
FAQ

The questions we hear most.

Can it be on-prem?+

Yes — many engagements use open-weight models running in your VPC or on-prem GPUs.

How do you handle IP and licensing?+

We track model and dataset licenses and only ship into commercial use cases with clean provenance.

What about copyright risk on outputs?+

We layer model choice, prompt patterns, and output filters to minimize regurgitation risk.

Related services

Most engagements span more than one practice.

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Ready to scope this in detail?

A 30-minute call with a senior engineer. No sales theatre — just a real assessment of fit, scope, and timeline.