Discipline 08 08

Artificial Intelligence.

Enterprise AI built on retrieval-augmented generation (RAG) - AI that answers from your own documents - and agents that complete real work inside your systems. We handle strategy, build, and training so your team owns the result.

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Abstract artificial intelligence visualization showing a glowing brain-like network of luminous nodes and particle streams in emerald, cyan, and violet on dark navy background. Artificial Intelligence
RAG Retrieval-Augmented Generation grounded in your private knowledge.
Agentic AI Goal-driven agents that plan, call tools, and act inside your systems.
Strategy · Build · Train Concept-to-scale lifecycle, with your team owning the result.
The new AI core

RAG and Agentic AI.
Where modern enterprise AI actually lives.

Generic chatbots are not enough. Real value comes from systems that know your company and systems that do work for your team. That is what we build.

Pillar 01

Retrieval-Augmented Generation (RAG)

Large language models grounded in your documents, policies, contracts, knowledge bases, and operational data - so answers are accurate, sourced, and current. No hallucinations from training cut-offs. No data leaving your perimeter.

  • Private knowledge ingestion - PDFs, SharePoint, Confluence, SQL, S3, ticketing, CRM, ERP.
  • Hybrid retrieval - vector + keyword + structured filters - tuned for your domain.
  • Citations on every answer, with the source chunk linked back to the original file.
  • Re-ranking, query rewriting, and guardrails to keep responses on-topic and safe.
  • On-prem, VPC, or sovereign cloud deployments. Your data never trains a public model.
Use cases

Enterprise search · policy & compliance assistants · technical support copilots · sales enablement · legal review · customer-facing AI grounded in product docs.

Pillar 02

Agentic AI

Goal-driven agents that don't just answer questions - they plan, call tools, and complete multi-step work on your behalf. Built on the same RAG foundation, wrapped in guardrails, observability, and a clear human-in-the-loop layer.

  • Tool use - the agent can call your APIs, query databases, run scripts, file tickets, send emails, and trigger workflows.
  • Multi-step planning with task decomposition, branching, and self-correction.
  • Multi-agent orchestration - specialists for research, writing, validation, and execution working as a team.
  • Memory - short-term conversational state and long-term grounded memory of past interactions.
  • Full audit trail of every step the agent took - what it read, decided, called, and produced.
  • Human-in-the-loop checkpoints for any action that touches money, customers, or production.
Use cases

Operations agents (triage, routing, scheduling) · research & analyst agents · sales SDR agents · back-office automation · underwriting and claims agents · engineering copilots that ship pull requests.

Together, these two pillars are how we ship modern enterprise AI. Everything else on this page - models, vision, predictive, recommender - either feeds them or extends them.
AI for Departments

One copilot per department.
Same stack. Different knowledge.

The same RAG and agentic foundation, scoped to one department's policies, contracts, SOPs, and tickets. Citations on every answer, an audit trail on every action, and your data never trains a public model.

Finance & Accounting

GL, AP/AR, contracts, vendor master, IFRS policy - answered with citations. Forecasting, anomaly detection, and reconciliation copilots with human-in-the-loop on anything that touches money.

HR

Policy Q&A, onboarding copilot, ticket triage, contract drafting. The handbook becomes a conversation; new joiners get answers in seconds, not days.

Legal

Contract review, clause comparison, redline assistance, prior-matter search. Counsel keeps judgement; the copilot does the reading.

Procurement

Vendor master Q&A, RFQ drafting, spend anomaly review, contract expiry alerts. Stops duplicate vendors and silent renewals before they cost real money.

Engineering & Operations

SOP copilot, equipment manuals on tap, work-order triage agent. Pairs naturally with Solace Stay Maintenance for forecasted maintenance schedules.

F&B

Menu engineering signals, recipe cost copilot, supplier-document Q&A. Turns invoices and recipes into a margin conversation, not a spreadsheet.

Pattern. Most clients lead with Finance, prove the pattern in one quarter, then add one new department per quarter. By year-end the head office runs on six copilots, all on the same backplane.
Full scope

Everything else we ship around RAG and Agents.

The classical AI practices that feed and extend the RAG and agentic core - the same teams, the same engineering bench, the same principle: domain knowledge first, modelling second.

RAG & Knowledge Systems

LLMs grounded in your private data with citations, hybrid retrieval, and on-prem deployment options.

Agentic AI & Tool Use

Goal-driven agents that plan, call your APIs, and complete multi-step work with full audit trails.

Recommender Systems

Custom suggestions for retail, content, sales, and ops - using AI and your behavioural data.

Predictive Analysis & Forecasting

Historical data turned into demand, churn, maintenance, fraud, and occupancy forecasts.

Custom ML Models

Classification, regression, clustering, ranking, vision, and NLP - the smallest model that meets the bar.

Chatbots & AI Assistants

RAG-grounded chatbots and assistants for customer support and internal productivity, with measurable uplift.

Computer Vision

Object recognition, classification, generation, and operational use - safety, retail, manufacturing QC.

AI Strategy & Training

Lifecycle consulting plus targeted programs to elevate your team's data and AI proficiency.

Lifecycle

How an AI engagement runs.

From the first concept to a model that operates at full scale - with your team riding alongside ours, learning to own it.

Strategy

Use-case discovery, ROI sizing, build vs. buy, and the data-and-talent maturity assessment that decides what is realistic this quarter.

Data Foundation

Data inventory, labelling, augmentation, and the engineering work that decides whether the model has a chance of working.

Modelling

Custom or fine-tuned, classical or deep, generative or discriminative - including RAG pipelines and agent orchestration. We pick the smallest model that meets the bar.

Deployment

Production deployment with monitoring, drift detection, agent observability, and rollback. Models and agents that operate, not just exist.

Training & Hand-off

Targeted training programs to elevate your team's data and AI proficiency - so they own the result the day we leave.

For Enterprise

Industries we focus on.

Pharma & Life SciencesR&D and commercial
InsuranceUnderwriting and claims
Learning & DevelopmentAdaptive learning
Enterprise & CorporatesInternal productivity
HospitalityGuest and ops AI
Public SectorCitizen services
RetailPersonalisation, vision
IndustrialPredictive ops, vision QC
Why Solace

Why teams trust us with the model.

01

Strategy first, hype last.

We will tell you when an LLM is the wrong answer, even if you came in expecting one. RAG only when retrieval helps. Agents only when they actually do work.

02

RAG and Agents that actually ship.

Production-grade retrieval pipelines, tool-using agents, evaluation harnesses, and observability - not weekend demos. Built to live in regulated, real-world systems.

03

Domain knowledge plus the maths.

The same teams build computer vision into Solace Iris and operations AI for Solace Stay. We ship in the real world.

04

Your team owns the result.

Training, documentation, and runbooks are deliverables - not afterthoughts. We hand the keys over.

Talk to us

Bring a use case.
Walk out with a lifecycle plan.

Book a demo sales@solacetech.group