All AI solutions

AI · LLM integration

Custom LLM integration,within your enterprise application stack.

Connect OpenAI, Anthropic, Azure, or open models to your app — with routing, caching, evals, and UX that keeps humans in control.

01 / Products shipped

250+

02 / Countries

30+

03 / Active clients

200+

04 / Building

8+ yrs

Custom LLM integration LLM integration with routing, security policy, and operational monitoring.

We scope llm integration engagements around measurable outcomes: task success, resolution time, or revenue lift — then ship in weekly increments with demos your stakeholders can evaluate.

What we typically ship for llm integration.

  1. 01

    Model routing & fallbacks

    Model routing & fallbacks with documentation, monitoring, and handover your engineering team can extend.

  2. 02

    Prompt & tool orchestration

    Prompt & tool orchestration with documentation, monitoring, and handover your engineering team can extend.

  3. 03

    RAG over your data

    RAG over your data with documentation, monitoring, and handover your engineering team can extend.

  4. 04

    Fine-tuning workflows

    Fine-tuning workflows with documentation, monitoring, and handover your engineering team can extend.

  5. 05

    Cost & latency controls

    Cost & latency controls with documentation, monitoring, and handover your engineering team can extend.

  6. 06

    Admin & analytics surfaces

    Admin & analytics surfaces with documentation, monitoring, and handover your engineering team can extend.

Intelligence for llm integration with guardrails.

  • 01 · AI

    Multi-provider gateways

    Multi-provider gateways designed alongside policy, evals, and fallbacks so production behavior stays predictable.

  • 02 · AI

    Structured outputs

    Structured outputs designed alongside policy, evals, and fallbacks so production behavior stays predictable.

  • 03 · AI

    Streaming responses

    Streaming responses designed alongside policy, evals, and fallbacks so production behavior stays predictable.

  • 04 · AI

    Safety & policy layers

    Safety & policy layers designed alongside policy, evals, and fallbacks so production behavior stays predictable.

Offshore depth, onshore clarity for llm integration.

  1. 01 · Edge

    Evals before launch

    We benchmark prompts, retrieval, and model routes against real tasks — not vanity demos.

  2. 02 · Edge

    Guardrails by default

    PII handling, refusal paths, rate limits, and human escalation are designed in, not bolted on.

  3. 03 · Edge

    Observable in prod

    Tracing, cost dashboards, and quality signals so you know when models drift or spend spikes.

  4. 04 · Edge

    You own the stack

    Prompts, pipelines, weights, and infra transfer at close — no black-box vendor lock-in.

See Our AI / ML engineering service for how engagements run.

Common questions about llm integration

  • Many pilots ship in 4–8 weeks after discovery, depending on data readiness and integration count.

  • Yes — we integrate hosted APIs, fine-tuned weights, or on-prem models your security team approves.

  • We design retention, redaction, and access controls up front — aligned to your compliance requirements.

  • We offer observability setup, eval refresh cycles, and optional managed support tiers.

Turn your roadmap into living AI products.

Tell us what you want to launch — we’ll outline a practical path from first prototype to production, with milestones you can track and no forced long-term contract.

Response time

Under 1 business day

Confidentiality

NDAs on request

First prototype

Often within a week