Solutions · AI & Automation
Put AI to work across your enterprise.
Help people find answers, assist service teams and automate routine work with Halo AI, configured around your processes by Nilantheon.
Illustrative simulation — not a product screenshot
Capability areas
Four places AI earns its place.
Capability statements verified against Halo's published Halo AI documentation (usehalo.com/halo-ai, July 2026). Items still on Halo's roadmap are labelled as such.
Conversational assistance
People get answers where they already work
Halo's conversational agents work across web chat, Microsoft Teams, Slack and the self-service portal — triaging and logging requests, guiding people to self-service, and escalating to the right person with full context. Each agent is shaped by a chat profile: persona, knowledge scope, tone, escalation logic and channel.
End-User Virtual Agent · Fulfiller Operations Agent · configured per team, department or user type
Illustrative
Intelligence within service workflows
Every ticket arrives with context
Platform intelligence learns from your service data: matched tickets and knowledge surface on new requests, and switchable AI suggestions help with categorisation, prioritisation, team routing and SLA-breach warnings. Unsupervised clustering surfaces recurring themes across high-volume processes.
Matched tickets & knowledge · AI suggestions · platform themes
Illustrative
New request
“Email not syncing on mobile since this morning.”
Reusable AI abilities
Start with proven abilities, extend to your own
A library of pre-built AI abilities — report analysis, satisfaction-survey sentiment, thank-you detection, knowledge-base creation — deploys straight into your environment. A native framework lets you embed reasoning in your own workflows for the cases the library doesn't cover.
AI report analysis · survey sentiment · thank-you detection · KB creation · build-your-own framework
Illustrative
Connections to external agents and systems
Part roadmapYour agents meet your service platform safely
Native MCP servers built directly inside Halo connect external agents such as Claude, Copilot and Codex, with per-agent tool selection and managed sign-in. The REST API exposes the full platform. Halo Skills and the Halo Blueprint semantic map are announced roadmap items — we plan for them, we don't promise dates.
Native MCP servers + REST API — released · Halo Skills & Blueprint — roadmap
Illustrative
External agents
Claude · Copilot · Codex
Halo platform
Permissions you define
Show the experience
Three moments where work moves differently.
Demo 1
Help employees find the next step
An employee asks a question, receives relevant knowledge, and can escalate with context attached.
Illustrative simulation — not a product screenshot
Employee
How do I request a laptop refresh?
Demo 2
Give service teams a head start
A request arrives summarised and categorised, with a suggested response ready for review.
Illustrative simulation — not a product screenshot
Summary
Payroll portal timing out for ~20 users since 09:12. All on the Bengaluru office network. No other locations affected.
Demo 3
Move routine work forward
A configured workflow checks conditions, routes work, and asks for approval where the rules require it.
Illustrative simulation — not a product screenshot
Trigger
New starter request submitted — Priya N., joining Finance, 4 Aug.
Customer control
Define what AI can see, suggest and do.
Halo AI operates inside your existing role-based access controls — each agent has an identity and permissions you define. Chat profiles set the knowledge scope, tone and escalation logic. Approval points in your workflows stay exactly where your policy puts them. And no AI response is treated as automatically correct: suggestions exist to be reviewed.
Level 1
Suggest
AI drafts, classifies and recommends. Nothing reaches a user or changes a record without the rules you set.
Level 2
Review
A person checks the suggestion, edits it, and decides. The default for anything customer-facing or risky.
Level 3
Act
Only within permissions you grant — for the routine, low-risk work you explicitly allow, with a full audit trail.
Not every action should be autonomous, and no AI response should be assumed correct. We configure the boundary with you — and write it down in the engagement plan.
Nilantheon's role
From AI capability to a working service.
01
Select the use case
One workflow, chosen for volume and value — never a platform-wide big bang.
02
Prepare knowledge and access
Curate the knowledge scope, data sources and permissions the capability is allowed to use.
03
Configure
Chat profiles, suggestions, abilities and workflow rules set up in a test tenant.
04
Test
Real scenarios against written acceptance criteria, including the cases it should refuse or escalate.
05
Launch
Live with a named owner and a rollback — users told what the AI does and where a person takes over.
06
Review
Weekly review of what it resolved, suggested and escalated — behaviour corrected, scope expanded deliberately.
Not sure which use case to start with? Take the 3-minute AI readiness self-score →
Your responsibilities
- — A named business owner who can approve the use case and its scope
- — Access to the knowledge and data sources in scope, with quality sign-off
- — People available for testing against the agreed scenarios
Acceptance criteria
- — The capability answers, routes or drafts correctly on the agreed test set
- — Escalation and refusal cases behave exactly as specified
- — Permissions audited: the AI sees only what the plan allows
Practical use case explorer
What this looks like in your department.
The problem
The queue repeats itself — password resets, access requests, the same network issue at the same branch.
Where AI assists
Conversational agent answers and logs; matched tickets surface known fixes; routine requests route automatically.
Where people retain control
Changes with blast radius, unusual incidents, and every approval the policy marks as human.
Systems & integrations
Halo ITSM, your identity provider, knowledge base, network monitoring telemetry.
The intended outcome
The desk spends its time on the work that actually needs an engineer.
Sound like your IT team?
Explore this use caseIllustrative scenarios — we don't publish performance figures we haven't measured with you.
Which workflow should AI help you improve first?
Explore your AI use caseA discovery session, not a sales call.