Spine is where Bill Gosling agents are built, tested, released and watched. Voice agents, live assist and quality scoring all run on it, share one record of every conversation and follow one set of rules. For a contact center leader that means one place to prove what the AI did and one place to change it.
Most AI projects stall between the pilot and the floor because nobody can show the agent is safe. Spine turns each release into the same five steps, so launching a new call type feels like a controlled change rather than a leap.
Persona, steps, guardrails and tools on a visual canvas, with a cost per call shown before launch. Your operations team can read the logic, not only engineers.
Synthetic callers try the easy paths and the hostile ones. Problems surface in a test run instead of in a complaint.
Conversation runs at machine speed. Anything that moves money or changes an account stops for a policy check or a named person.
Every decision lands on a tamper-evident log mapped to the frameworks your auditors use. Evidence is ready before anyone asks.
Live calls are scored continuously. Drift shows up on a dashboard and the next version goes back through the same steps.
Run Spine with your own team or with Bill Gosling supervisors, QA leads and specialists who sign up to the result.
Every agent family sits on the same foundations, so a rule you set once applies to the voice agent, the assist panel and the QA scorecard alike.
A step canvas for the conversation, with guardrails, actions, variables and tools imported over MCP. Every version is kept and any one can be restored. Why it matters: changes to scripts and policy reach the floor in days, with a way back.
Know more →Synthetic callers, adversarial scenarios, golden-call regression and rubrics, then a ramp gate that only widens traffic while scores hold. Why it matters: fewer surprises after launch and a clear record of why a release went live.
Know more →Each task goes to a model chosen by cost, latency and risk, from open-weight models on our own Google Cloud GPUs to commercial models. Why it matters: cost per contact you control and no lock-in to one model vendor.
Know more →Intents, sentiment, outcomes and compliance events captured from AI and human conversations alike. Why it matters: every agent and every report works from the same facts.
Know more →A live floor dashboard, a fleet control room across products and NEQQO dashboards for leaders. Why it matters: problems are spotted during the shift, not in next month’s review.
Know more →Telephony and CCaaS, CRM, core banking and loan systems, payments including UPI, knowledge bases, MCP, webhooks and a workflow engine. Why it matters: agents act on real data without a rip and replace.
Know more →Write gate, audit chain, redaction, tenant isolation, consent checks and a Compliance Center with an always-on Guardian agent. Why it matters: compliance risk goes down as automation goes up.
Know more →When the voice agent, the assist tool and the QA tool share a brain and a record, a handover keeps its context and a report tells one story.
A disclosure rule or a contact window is set once and enforced on every channel and every agent.
AI turns and human turns are scored, audited and reported together, so nothing falls between systems.
Update an agent in Studio, test it in simulation and ramp it behind a gate, with rollback always one step away.
In the demo we build a step in Studio, run it past synthetic callers, take a live call and open the audit entry it leaves behind.