One ticket. Ten capabilities. One platform.
Restart the agents. Reconnect the core application. Fix the input file. Re-run the batch. Answer the requester. SupportFlo does all of it on one platform — because a support ticket never respects the boundary between your monitoring tool, your ITSM and your bots.
Every tool you own covers one spoke
That is why a ticket that should take four minutes takes forty, and touches three teams on the way.
Alerts, but cannot fix
It tells you the node is at 98% CPU at 2 a.m., accurately and instantly.
Then it waits for a human to read the alert, open a session and do something about it.
Logs, but cannot act
It routes, prioritises and reports on the ticket perfectly.
It cannot reconnect your core application, clear a green-screen pop-up or move an output file.
Acts, but cannot decide
It runs the restart script flawlessly, every time you tell it to.
It cannot read a free-text email, work out which of nine faults this is, or choose the right runbook.
SupportFlo is the whole wheel. Read, diagnose, act, verify, respond — the ten capabilities below are one platform, not ten products you integrate.
Follow one ticket around the wheel
A core-application disconnect, a server restart, a data request. Select any capability on the wheel to see the part it plays.Here is the part each one plays.
Agentic AI
Reads each ticket, diagnoses the fault and decides the path: self-heal now, run the approved runbook, or escalate to L2 with the diagnosis attached.
In the queue“Agents stopped on server 172.27.42.204 after last night’s reboot” — recognised as a post-restart pattern and sent straight to the restart runbook.
Select a number on the wheel, or use the arrow keys.
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1
Agentic AI
The L1/L2 brainReads each ticket, diagnoses the fault and decides the path: self-heal now, run the approved runbook, or escalate to L2 with the diagnosis attached.
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2
Conversational
Email, Teams & WhatsApp intakeTickets arrive as free text. The agent understands them, acknowledges immediately, and asks for whatever is missing instead of waiting for a human to ask the obvious.
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3
Human-in-loop
Engineers on the hard 10%Script errors, database faults and anything needing genuine root-cause analysis go to an engineer — with logs, server state and ticket history already gathered.
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4
EdgeAI Copilot
Adapt at ops speedWhen a new server, batch or ticket category appears, an ops lead describes the runbook in plain English and it goes live. No development cycle.
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5
Document AI
The readerParses messy ticket text, screenshots and attachments to pull the exact operational entities — server IP, application number, file path, error string, batch name — then classifies category and sub-category.
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6
Integrations & ITPA
Wired into the estateConnected to the systems the queue actually lives in: the ITSM tool, the core business application, cloud, file shares, mail and the monitoring stack.
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7
RPA
Hands on legacy & GUIWhere there is no API, the agent does what an engineer does on screen: restarts agents on a server, reconnects a dropped session, clears a green-screen pop-up, resets a directory password.
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8
ETL
Data & file plumbingValidates and repairs input files, moves outputs to the right path, resolves path-not-accessible errors and fulfils data requests.
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9
Workload Auto
Run and watch the batchesSchedules, monitors and re-runs batch and bot jobs, adjusts frequency on request, handles backdated executions, and raises the alert the moment something drifts — 24×7.
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10
AgentEdge
Pre-built, live in weeksShips with a runbook and category-action library for IT support — core-app reconnect, agent restart, data-request fulfilment, file repair — so you tune to your estate instead of building from zero.
Logged to resolved, without changing hands
Five stages. Each one draws on whichever capabilities the ticket actually needs — no hand-offs between products, no queue between steps.
Intake & triage
The ticket lands by email, Teams or WhatsApp. The agent reads it, extracts the operational entities and classifies category and sub-category.
Diagnose
Pull server, application and monitoring state; find the root cause — a dropped core-app session, agents down after last night's reboot, a runaway query.
Remediate
Run the approved runbook: restart the agents, reconnect the core application, clear the pop-up, repair the input file or path, reset the password.
Verify & fulfil
Confirm the job or session is healthy, deliver the data request or output file, and keep watching the run rather than declaring victory early.
Respond or escalate
Update and close the ticket with notes and reply to the requester. Script errors, database faults and genuine RCA go to an L2 engineer, fully briefed.
Every capability earns its place on a single ordinary ticket. Take any one of them away and the ticket stops somewhere and waits for a person.
The work is more repetitive than it looks
A representative infrastructure and application support queue from a live enterprise deployment — roughly 1,150 tickets, around four in five arriving as free-text email.
Relative volume by ticket category. Generalised from a live enterprise automation-ops queue; category names normalised.
Read the shape of it
Only the last row is genuinely hard. Everything above it is a known fault with a known fix, arriving as free text, repeating week after week — and being handled by hand because no single tool can read it, decide on it and act on it.
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The top row is the biggest prize“Agent started manually” after a restart is the highest-volume ticket type in most estates — and it is fully hands-off on day one.
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Most “IT tickets” are data problemsWrong file, missing file, unreachable path, output not shared. Nothing here needs an engineer, and all of it eats L1 hours.
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Your engineers keep the bottom rowScript errors, database faults and root-cause analysis reach a human with logs, server state and history already attached.
Answering a ticket is not closing one
Conversational front ends are good at replying. The question that decides your cost per ticket is what happens next — when the request needs something done in a real system.
| Capability | ITSM | Monitoring | Chat / AI front end | Standalone RPA | SupportFlo |
|---|---|---|---|---|---|
| Reads a free-text email ticket | — | — | Yes | — | Yes |
| Decides which fault this is | — | — | Routes only | — | Yes |
| Acts on legacy & GUI systems | — | — | Add-on module | Yes | Yes |
| Repairs files & fulfils data requests | — | — | — | If scripted | Yes |
| Schedules, watches & re-runs batches | — | Alerts only | — | — | Yes |
| Verifies the fix actually held | — | Alerts only | — | — | Yes |
| Closes the ticket & writes the notes | Manually | — | Sometimes | — | Yes |
| Governed, audited, human-in-the-loop | Yes | — | Varies | — | Yes |
The moment a request needs real backend action, most platforms hand off to a second product you license and integrate separately. SupportFlo builds the execution layer into the same platform that handles the conversation.
Autonomy you can actually sign off
Every ticket travels a four-layer governed stack, not one model making unchecked calls on production.
AI Control Tower
Resolution analytics, human-in-the-loop routing, a full audit trail and real-time visibility of what every agent did and why.
Orchestration & Policy Guard
A manager agent routes intent to the right specialist; Policy Guard validates every action against your rules before it runs.
AI specialist agents
Directory, access, network, endpoint, software and infrastructure agents — each executing within its own defined scope.
AI models
Conversational AI, retrieval over your own documentation, and machine-learning triage and routing.
Outcomes from live enterprise deployments
Not claims — real metrics, at real scale, on the ITSM these teams already run.
Teleperformance
BPO · IT access management · 28,000 employees Day 1 New-hire access creation, down from up to 5 business days- 15+ HR and IT processes automated
- Eliminated labour-lawsuit exposure
- < 4 months to full deployment
Genpact
Global BPO · IT shared services · 90,000+ employees 99.17% Cycle-time reduction per request- 140,000+ tickets resolved in 21 months
- 48,000 requests a month automated
- 14 FTE freed for client work
Wipro
IT services · managed services · 250,000+ employees $2M+ Validated hard-ROI savings across the IT estate- 140 bots in production, running 24×7
- 9,000+ compliance tickets a month
- 15+ FTE redeployed
UMMS
Healthcare · ITSM · 45,000+ users · 11 hospitals 80% Helpdesk workload cut on directory password resets- ~1 min call turnaround, from 45
- 98–99% reset success rate
- 100+ concurrent transactions
Tune it to your estate, don't build it
SupportFlo ships with a runbook and category-action library for IT support, so the first weeks are configuration rather than development.
Connect the ITSM, identity, mail and monitoring stack. Point the agent at the live queue.
Configure your top ticket categories and run in shadow mode — the agent decides, your team still acts.
Go live on the highest-volume categories: agent restarts, core-app reconnects, file repairs, data requests.
Add categories in plain English as new servers, batches and applications appear. No development cycle.
Two ways to buy — you pick the economics
Start with zero procurement risk, or run it as a predictable line item.
Outcome-based
Resolved IT ticket- You pay only when a ticket actually closes
- Zero procurement barrier — the pilot is free
- The pilot builds its own ROI case on your tickets
- 70–80% below typical outsourced cost per ticket
Subscription
Annual, all-inclusive + LLM cost- A single, CFO-friendly line item
- Fully managed LLM infrastructure
- Multi-year discounts available
- Transparent, disclosed pricing — no metered token pool
Questions infrastructure teams ask first
No. SupportFlo sits on top of the ITSM you already run — ServiceNow, BMC Helix, Jira Service Management, Freshservice, ManageEngine or an in-house tool. Your ITSM stays the system of record; SupportFlo becomes the system of action and writes every step back to the ticket.
That is exactly the case RPA covers here. Where there is no API, the agent does what an engineer does on screen — restarts agents on the server, reconnects a dropped session, clears a green-screen terminal pop-up, resets a directory password, works a vendor portal. Conversation, API automation and screen-level execution are all in the same engine, so automation does not stall at the first system without an interface.
Policy Guard validates every action against your rules before it runs, and only actions you have classified as safe execute autonomously. Anything carrying risk — a production restart, a configuration change — pauses and raises a human-in-the-loop request with the full diagnosis attached. Every decision and action is written to an audit trail in the AI Control Tower.
One to two weeks for tier-1 categories. The runbook and category-action library ships pre-built for IT support, so the work is connecting your systems and tuning to your estate rather than building agents from zero. New categories after that are described in plain English and go live without a development cycle.
They reach an engineer faster and better prepared than they do today. Script errors, database faults and anything needing genuine root-cause analysis are escalated with logs, server state, ticket history and the agent's own diagnosis already gathered. The aim is not to remove your engineers — it is to stop them spending the day on agent restarts and password resets.
Yes. A two-week pilot runs on your real queue, starting in shadow mode so you can compare the agent's decisions against your team's before it acts on anything. On the outcome-based model you pay per resolved ticket, so the pilot builds its own business case rather than asking you to fund one.
Put your own queue on the wheel
Send us the shape of your ticket volume and we'll come back within one business day with what SupportFlo would take off it.
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