Knowledge assistants
Find, summarize, and cite information from approved documents, policies, and records, with source references for checking.
AI solutions
Custom AI Agents Built around your work.
We design, build, and operate AI agents that understand your business: agents that research, draft, decide, and act across your systems, with the guardrails, evaluation, and human oversight that enterprise work demands.
Scope, delivery, and pricing are agreed for your organization. Prefer email? Enquire
- Built around
- Your tasks, knowledge, and tools
- Connects to
- ERP, CRM, email, and documents
- Oversight
- Human approval where it matters
- Models
- Commercial or open-weight
Overview
AI that works the way your organization does
An AI agent combines a language model with your approved information sources and connected tools to carry out defined tasks. We design each agent around a real workflow: what it can access, what it can do, and when a person should take over.
The result is an agent your teams can trust, one that takes on repetitive knowledge work while keeping people in control of the decisions that matter.
- Scoped to a defined workflow and measurable outcome
- Connected to your systems within agreed permissions
- Evaluated against representative tasks before launch
- Human review built in wherever decisions matter
Capabilities
What we deliver
The core capabilities of Custom AI Agents, shaped around your workflows and systems.
Workflow agents
Triage requests, prepare documents, and coordinate multi-step processes across your systems, pausing for approval where required.
Document processing
Read contracts, specifications, and forms, extract what matters, and prepare structured outputs for your team.
System-connected agents
Work inside ERP, CRM, and internal tools through secure, permissioned integrations with full logging.
Customer and partner support
Answer common questions and route complex cases to the right person with the full context.
Analysis and reporting
Assemble information from several sources, draft recurring reports, and highlight exceptions for review.
Technology
The technology behind it
We use proven, well-supported technology and choose it for each engagement. These are the platforms and tools we most often bring to Custom AI Agents work.
Foundation models
We choose models per task, weighing accuracy, speed, cost, and where your data is allowed to go.
- Anthropic Claude
- OpenAI GPT models
- Google Gemini
- Meta Llama
- Mistral
- Azure OpenAI Service
- Amazon Bedrock
Agent orchestration and tools
Agents reach your systems through typed, permissioned tools rather than open-ended access.
- Model Context Protocol (MCP)
- LangGraph
- Semantic Kernel
- Temporal
- Python
- TypeScript
Knowledge and retrieval
Answers are grounded in your approved sources, with citations your team can check.
- PostgreSQL + pgvector
- Azure AI Search
- Elasticsearch
- SharePoint and Microsoft Graph
- Hybrid keyword and vector search
Evaluation and observability
Every agent ships with a test set built from your work and is monitored in production.
- Task-based evaluation suites
- OpenTelemetry
- Langfuse
- Human review queues
- Audit logging
Final technology choices are confirmed during scoping, based on your existing systems, security requirements, and budget. Product names are trademarks of their respective owners; listing them does not imply a partnership.
How we deliver
A clear path from idea to impact
Every engagement follows the same disciplined path, sized to your needs, with agreed scope, milestones, and success measures.
Discover the workflow
Identify the users, tasks, tools, and outcomes the agent should support, and agree how success will be measured.
Design the agent
Define approved knowledge sources, tool permissions, guardrails, and the points where people review or approve.
Build and evaluate
Test the agent on representative tasks, including edge cases and situations where it should ask for help, then refine.
Deploy and improve
Launch with monitoring, logging, and documentation, and keep improving as your processes and models evolve.
Why EngLogics
What you gain by working with us
Technology is only part of the answer. These commitments shape every Custom AI Agents engagement, and they are why organizations choose a specialist partner.
Designed around a measurable outcome
We start from a workflow and a number that matters, such as turnaround time, hours recovered, or error rate, and design the agent to move it. Not a chatbot looking for a problem.
Model-agnostic by design
We are not tied to one AI vendor. As models improve and prices fall, your agents can move to better options without a rebuild.
Controls your risk team will approve
Least-privilege tool access, approval steps, full audit trails, and data residency options are designed in from the first workshop.
Fluent in technical work
Our team understands quoting, specifications, drawings, and operational data, so agents are designed for the edge cases your specialists actually face.
Built for enterprise
Designed to be trusted
Security, oversight, and maintainability are part of the design from the first conversation, not added at the end.
Human in the loop
Actions that matter wait for a person to review and approve them.
Least-privilege access
Agents can only reach the systems and data they are permitted to use.
Evaluated before launch
Behaviour is tested against your real tasks and agreed criteria.
Full audit trail
Every step an agent takes can be logged and reviewed.
Outlook: the future of AI
From assistants to a digital workforce
AI is moving from answering questions to carrying out multi-step work across business systems. The organizations that benefit most will be the ones that build the foundations now: governed access to their data, well-defined tools, and oversight that lets agents take on more responsibility safely.
- Now
Agents that research and draft
Agents prepare quotes, summaries, and reports for people to review. The value is hours returned to your specialists.
- Next 2–3 years
Agents that coordinate work
Several agents pass work between each other and across systems, escalating exceptions to people instead of every step.
- Longer term
Agents in the operating model
Routine processes run continuously under supervision, and teams spend their time on judgment, customers, and improvement.
Questions
Before we begin
Bring a description of your current process, the systems involved, and the outcome that would matter most to your team.
What is a custom AI agent?
An AI agent uses a model, agreed information sources, and connected tools to support a defined workflow. Its tasks, permissions, and review steps are designed around your business.
Can it work with our existing tools and documents?
Share the systems and information sources you want to use. We review access, integration options, data handling, and any restrictions as part of scoping.
Where does human review fit?
We define which actions need approval, how people can check outputs, and when the agent should hand work back to your team.
Which AI models do you use?
We select models for each use case, including commercial models through enterprise endpoints and open-weight models that can run in your own environment.
How are costs and ongoing support handled?
Development, hosting, AI usage, maintenance, and support needs are discussed for your project. Pricing and delivery depend on the agreed scope.
Start a conversation
Let’s put AI to work on your processes
Tell us about the workflow, the systems involved, and the outcome you need. We will respond with practical next steps for scoping your project.