LLM Integration Services

Turn LLM experiments into reliable production systems

Prioritise LLM initiatives by business impact, risk, and feasibility
Design secure, observable architectures that scale beyond PoCs
Embed LLMs into products and processes with measurable outcomes

When our LLM integration services are right for you

Best suited for organisations that are beyond basic experimentation and need a structured, accountable way to scale LLM use.

You have multiple LLM pilots but no cohesive strategy

You’re running scattered experiments across teams and need a unified roadmap, standards, and governance model.

You need to move PoCs into production safely

You have promising prototypes and now require secure, observable, and supportable production implementations.

You own complex products or workflows

Your products or operations have rich domain logic and data, and you need LLMs to work reliably in that complexity.

You care about compliance and brand risk

You operate in regulated or brand‑sensitive environments and must manage data privacy, safety, and output quality.

You want measurable business outcomes

You expect clear KPIs—cycle time reduction, cost savings, revenue lift—not just ‘AI innovation’ slides.

You have engineering teams but need LLM expertise

Your teams can build and run software, but you need specialised support on LLM patterns, tooling, and best practices.

You’re modernising your data and application stack

You’re investing in data platforms, APIs, or cloud migration and want LLM capabilities designed into that roadmap.

You want to empower, not replace, your people

Your goal is to augment teams with copilots and smarter workflows, with clear change management and training.

You need a pragmatic, no‑hype partner

You prefer a delivery partner who speaks in trade‑offs, risks, and ROI—not generic AI evangelism.

Example use cases

Where LLM integration delivers tangible value

B2B SaaS

Intelligent customer support copilot

Integrate an LLM‑powered assistant into your support console to summarise tickets, suggest responses from your knowledge base, and propose next best actions—reducing handle time while maintaining compliance with tone and policy.

Professional Services

Sales content and proposal generation

Use LLMs to assemble first‑draft proposals, RFP responses, and sales emails from approved templates, case studies, and pricing rules—shortening sales cycles and improving consistency without bypassing review controls.

Financial Services

Operational document understanding

Deploy LLMs to extract key terms, risks, and obligations from contracts, policies, and regulatory documents, feeding downstream workflows and dashboards while maintaining a human‑in‑the‑loop review process.

Technology

Developer productivity and knowledge search

Integrate LLM‑backed search across code, architecture docs, and runbooks so engineers can ask natural language questions and receive grounded answers with links to source—reducing onboarding and incident resolution time.

Manufacturing & Logistics

Personalised self‑service portals

Embed LLM chat and guided flows into customer or partner portals to answer product questions, track orders, and trigger service requests—integrated with your CRM and ERP for accurate, real‑time responses.

Our approach

From roadmap to production‑grade LLM integration

We combine AI strategy, architecture, and delivery to move you from scattered pilots to a coherent, governed LLM capability embedded in your stack.

1. Discovery & value mapping

Work with your product, engineering, and business leaders to map current workflows, pain points, and data assets. Identify and score LLM opportunities by business value, technical feasibility, risk, and change impact.

2. Solution design & architecture

Define the right LLM patterns for your context—RAG vs. fine‑tuning, prompt orchestration, safety layers, and human‑in‑the‑loop. Design reference architectures that align with your cloud, security, and data strategies.

3. Pilot build & validation

Implement a focused pilot with clear success metrics. Integrate with your systems, instrument evaluation frameworks, and run structured testing for quality, latency, cost, and failure modes before broad rollout.

4. Production integration & hardening

Industrialise successful pilots: build APIs, services, and UI components; add monitoring, logging, guardrails, and fallback paths; implement access control and auditability; and align with your SDLC and MLOps practices.

5. Rollout, enablement & continuous improvement

Plan staged rollout, train end‑users and support teams, and establish feedback loops. Continuously refine prompts, models, and data sources based on usage analytics and evolving business goals.

Business Outcomes

Clear LLM roadmap tied to business outcomes and ownership
Robust, secure architectures aligned with your cloud and data strategy
Faster path from PoC to production with controlled risk and cost
Improved productivity and experience across targeted workflows
Foundations for ongoing LLM innovation, not one‑off experiments

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