For technology and software companies

Task Intelligence for technology operations

Three canonical tech ops patterns, redesigned at the task level. Incident response, deployment management, tier-2 support. Hours freed per engineer, throughput 2 to 3x, same observability stack, same SRE envelope. Plus live AI redesign of four tech workflows.

152,000
Real job postings analyzed
620
Companies in dataset
2.1M
Tasks classified
0
Technology tasks ready for AI augment
Jobs view

Three roles in tech ops, redesigned at the task level

Every tech ops desk has the same task shape: read log or alert data, cross-reference service maps and prior incidents, draft a remediation or escalation, human reviews. Each role below keeps doing the work — AI takes the load on the routine tasks. Hours freed, throughput up, same SLOs.

Where AI cowork lands first in tech ops

0 technology tasks where the AI takes the load and the human stays on the decision. Pulled live from our task taxonomy. The top 0 are below. 0 more are ready for full automation, expand the list to see them.

0 technology tasks ready for full automation

How we work with tech orgs

Co-sponsored model. Functional head (VP Engineering, VP Platform, Head of SRE, CTO) plus your transformation office in the room. Sprint proves the redesign in 90 days inside one engineering function. Transformation Engagement scales across the operating model — same observability stack, same SLOs.

Sprint
90 days
One engineering function, three tasks redesigned
Transformation Engagement
Custom
Operating-model redesign across SRE, DevOps, support, engineering productivity
Implementation
Same stack
Same engineers, same observability and CI/CD, AI cowork layer on top

Want a tech-specific walkthrough?

20 minutes. We pull your top three task patterns from the dataset and show you the redesign live, with your role mix and your SLO frame.

Book a time