Each worker handles a single call, so a stuck or crashed worker can only ever lose one call, never a batch.
The platform · 4th generation
One system, from dial to disposition.
Everyone else sells you a layer. We run the whole call. Oriserve dials or answers, holds a real conversation, hands the hard moments to a person with the context attached, and returns a recorded, analysed, scored, dispositioned record to your systems. One platform, built to run at fleet scale.
Voice fleet · liveSimulation
calls in flight0
resolved by AI0
to a person0
resolved by AIhanded to a person
"A contact centre is not a technology problem. It is a consistency and learning problem. So we did not build a tool; we built the system that runs the whole call and remembers every one."The platform doctrine · own the loop, not a layer
Why one system beats a stack of tools
A dialler, a bot, an analytics tool and a QA vendor do not add up to a contact centre. The seams are where outcomes leak.
Stitch four vendors together and the bot never tells the agent what it learned, the QA tool scores 5% of calls after the fact, and nothing improves the next call. The intelligence falls through the gaps between tools.
Oriserve is one system. The control plane owns the durable truth, every bot, every campaign, every call record; the runtime plane does the real-time work and keeps no state, so it scales out and a crashed worker costs you exactly one call. What the whole thing learns, it keeps.
The life of a call
Two call shapes, one pipeline, one record.
Whether the platform dials out or the customer dials in, every call runs the same path and returns the same complete record.
Begin
Dialled or answered
The dialler places a paced outbound call, or a customer rings a configured number. Both arrive at the telephony plane.
Pick up
One worker, one call
The call lands on a single free worker, which fetches this bot's live config: prompts, voice, tools, and the customer's CRM data.
Converse
The speech loop runs
Listen, reason, speak, in real time, with turn-taking and interruption handled, the whole conversation recorded.
Decide
Resolve or hand over
The AI closes what it can; the calls that need judgement route to a person, briefed, in seconds.
Finalise
A scored record, returned
Transcript, analysis, QA findings and a disposition are packaged and pushed back to your CRM.
Under the hood
Four services, one clean split.
A control plane that owns everything durable, and a runtime plane that does the real-time work and holds no state. That split is what makes the platform both reliable and scalable.
Control planeBackend
The source of truth
Auth, bots, campaigns, per-call config, every durable call record, CRM integrations and recordings. If it must survive a restart, it lives here.
Operator surfaceConsole
Point-and-click control
The dashboard your team runs: bot builder, campaign builder, call logs, reports, knowledge bases. No engineering needed to launch a campaign.
Runtime planeVoice fleet
Disposable muscle
Live call workers and the speech pipeline. Stateless by design, so it scales out horizontally and any worker can take any call.
Execution planeDialler
Paced outbound at scale
Predictive pacing, retry scheduling, outbound SIP and answering-machine screening, so the fleet and your carrier are never overrun.
The defining split
Config flows down. Results flow up.
The whole system turns on one loop: the control plane hands each call its config, the runtime plane runs the call and hands back a complete record. The workers in between keep no state, which is what makes it both scalable and hard to break.
Built for the floor, not the demo
Scale that a contact-centre head can actually trust.
Blast radiusOne call
Scale1M+ calls/day
Workers are stateless and re-fetch config each call, so capacity grows by adding hosts.
PacingPredictive
The dialler paces outbound so it never overruns the fleet or the carrier, with answering-machine screening built in.
Audit100% of calls
Every call recorded, transcribed, analysed and scored, where the industry samples under 5%.
Why it gets better
Every call is scored, and the score feeds the next call.
Because one system runs the bot, the routing and the QA, what the platform learns on your book does not leave with an agent or sit in a report nobody reads. It is captured, scored and returned to the model.
The voice bots and intelligent routing run this loop in production today. The agent copilot and the continuous self-learning layer are in build, Aug 2026, and deepen it further.
Honest about what is live
What runs today, and what is next.
AI voice botsLiveHandle the bulk of calls end to end
Across voice and chat, in the customer's language, in production at scale.
Intelligent routingLiveThe warm handoff to a person
Hard calls routed with intent, sentiment and history attached.
Agent copilotIn build · Aug 2026Real-time help for humans
Suggestions, offers and compliance prompts, from the same brain as the bot.
Self-learning loopIn build · Aug 2026Every call retrains the model
QA and outcome data ingested continuously, so automation compounds.
Security & compliance by construction
The controls a regulated buyer asks for first.
Controls under infosec confirmation; the architecture puts them in the platform, not the policy document.
ResidencyData resident in India
Customer and call data held in-region, with recordings encrypted and access-controlled.
CertificationISO 27001:2022
Certified information-security management, with SOC 2 and ISO 42001 on the trust roadmap.
AccessMFA & VPC isolation
Multi-factor access and network isolation on a private cloud footprint.
TelephonyTRAI-compliant dialling
Contact windows, frequency caps and DND checks enforced before an outbound call is placed.
PaymentsPCI-DSS handling
In-call payment links kept inside the standard; card data never lingers in a transcript.
AuditThe whole book, retrievable
Every call recorded and scored, so your audit answer is the entire book, not a sample.
Go deeper
The two parts that make it work.
The agents
Conversations that hold up
A speech pipeline that handles real Indian speech, grounds every answer in your data, and acts inside the call. See the AI agents →
The handoff
Where AI meets a person
The moment a call needs judgement, it moves to a human in seconds with the full context. See the handoff →
What a contact-centre head asks before signing
Does this rip out my dialler, CRM and telephony?
No, it connects to them. The platform integrates with your CRM and telephony stack, reads and writes to your systems of record, and can run alongside what you have. You are not forced into a rip-and-replace to get value.
What actually happens if a call fails mid-conversation?
You lose that one call, nothing else. Each worker runs a single call and holds no state, so a crash never takes down a batch, and the dialler's retry logic re-approaches the contact. The design assumes failure and contains it.
Is our data mixed with other customers' data?
No. Your data stays yours, resident in India, and what the platform learns on your book improves your book. Tenancy detail ships in the security pack.
How do you handle Indian languages and real phone-line audio?
With a speech pipeline built for it. Speech recognition and low-latency voice across 10+ Indian languages, with mid-call switching and interruption handling, tuned for the accents and line conditions generic engines struggle with.
How fast can we go live?
A production pilot on your real calls, with first live results by Day 7. Integration depth decides the exact timeline; the baseline is agreed before the first call, and the console lets your team build and launch without engineering.
How is it priced?
Consumption on handled volume, plus a success fee on the outcome above your baseline. No seats; the full construct is on the outcome pricing page.
See the system run
Put a real call through it. Watch the whole loop.
The platform · watch it work
Follow one call through the machine.
Full-screen · ~35 seconds · simulation · esc exits