Internal
Answers grounded in your own documents
Staff ask in plain language and get an answer with the source passage attached, scoped to what their role is permitted to see.
Custom AI Agents & Assistants
AI systems built on your processes, not a generic chatbot widget.
We build assistants and agents that work inside your business: grounded in your documented knowledge, bound by your rules, connected to your systems, and designed to escalate to a person when they should.
What this is
Put institutional knowledge and routine decisions within reach of everyone.
A useful business agent is mostly engineering, not prompting. It needs a reliable source of truth, a retrieval layer that finds the right passage, permissions that respect who is allowed to see what, tools it can call to actually do something, and a clear boundary where it hands off to a human.
We build that whole stack, including the unglamorous parts: how documents get indexed and refreshed, what the agent does when it is unsure, how you review what it said, and how you correct it when it is wrong.
Problems this addresses
Signs this is the right next step.
The answer exists in a document nobody can find quickly.
New hires take months to become self-sufficient on process questions.
Support answers the same questions repeatedly with inconsistent detail.
Off-the-shelf chatbots cannot see your internal systems or records.
A general AI tool confidently gives answers that are wrong for your business.
There is no record of what an AI tool told a customer or an employee.
Capabilities
What the engagement covers.
Scope is agreed in writing before work starts. Not every engagement includes every item below — the mix is set against your constraint.
- Internal knowledge assistants
- Customer-support agents
- Sales and lead-qualification agents
- Research assistants
- Employee onboarding assistants
- Document-processing agents
- Operations assistants
- Multi-step agentic workflows
- Human approval and escalation systems
Business use cases
Where this creates value.
Customer-facing
Support that knows your policies
Handles the repeat questions using your actual policy language, and hands the conversation to a person the moment it hits an exception.
Revenue
Qualification before a human call
Inbound enquiries are asked the qualifying questions, enriched, summarized, and routed — so the first human conversation starts informed.
Back office
Document intake at volume
Extracts structured fields from contracts, forms, or invoices, flags low-confidence extractions for review, and writes clean records into your systems.
Implementation
How the work runs.
Each phase produces something you can review. Progress is demonstrated in working software and written decisions rather than status updates.
Scope
Define exactly what the agent is responsible for, and just as importantly what it is not.
Ground
Assemble and structure the source knowledge, set permissions, and define the tools it can call.
Build
Implement retrieval, business rules, escalation paths, and logging, then test against real questions.
Review
Measure accuracy on a held-out set, correct the failure modes, and set the ongoing review cadence.
Technology and integration
Model choice follows the requirement — accuracy, latency, cost, and data-handling terms — and is documented so it can be revisited as the market moves. Agents connect to your systems through scoped APIs, not shared logins.
Security and governance
Agents see only the data their role requires, and permissions are enforced at retrieval rather than by instruction. Prompts and outputs are logged so any answer can be audited, and any action with real consequence sits behind a human approval step by default.
Our security approachQuestions
About custom ai agents and assistants
By grounding answers in retrieved source material, requiring citations back to the source, constraining scope, and testing against a set of known questions and correct answers before release. We also measure and report where it fails rather than claiming it does not.
Not under the configurations we deploy. We use business-tier API access where the provider's terms exclude training on your inputs, and we document exactly which provider handles what data.
Both. Actions — creating a record, sending a message, scheduling — are implemented as explicit tools with permissions, and anything consequential sits behind a human approval step unless you decide otherwise.
Refreshing the knowledge source as documents change, reviewing flagged conversations, and periodically re-testing accuracy. We can hand that over with documentation or run it as part of a managed engagement.
Related capabilities
What this usually connects to.
Business Process Automation
Cut the manual handoffs that slow every process down.
Explore this serviceCustom Software & Application Development
Stop bending your process to fit software built for someone else.
Explore this serviceManaged Technology & Optimization
A technology partner who is still there in month six.
Explore this serviceTell us what this process costs you today.
We will give you an honest read on whether custom ai agents and assistants is the right next step, and what a first engagement would involve.