Specialised · under AI Development
LLM Application Development Services
Most LLM demos can't survive production. We build LLM applications with evaluation harnesses, cost monitoring, prompt versioning, guardrails and provider fail-over — engineering, not prompting.
What we build
- Provider integration (OpenAI / Anthropic / Gemini / self-hosted)
- Prompt design and versioning
- Streaming UI with abort + retry
- Evaluation harness with golden datasets
- Cost monitoring per request
- Rate limiting and queueing
- Guardrails for safety + hallucinations
- Multi-provider fail-over routing
- Caching and prompt result reuse
- Audit logs of every AI decision
What you receive
- Production LLM application
- Evaluation harness for prompt regression
- Cost dashboards per workflow
- Documentation of prompt versions
- Retainer for ongoing prompt tuning
Why custom over off-the-shelf
Production AI is engineering
Evaluators, guardrails, regression testing, cost monitoring — these are not 'add later'. They are why your AI product doesn't break the week after launch.
Provider lock-in costs money
We architect with fail-over routing so we can swap providers as their pricing and capabilities shift. Single-provider AI products are paying tomorrow's premium.
Pricing and timeline
Price range
$15,000 – $60,000
USD, fixed-cost after written scope
Timeline
6 – 12 weeks
From kickoff to production
FAQ
Which LLM should we use?
Depends on cost, latency, task and data sensitivity. OpenAI for breadth. Anthropic for long-context, safety and HIPAA-friendly via Bedrock. Gemini for Google ecosystem integration. Open-weights when self-hosting matters.
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See details →Ready to scope this?
Fixed-cost proposal and delivery plan within 48 hours of a 30-minute discovery call.
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