Product plus dedicated expertise
Tensile is the reliability workspace your team uses and the evidence it keeps. Dedicated human engineering and AI-assisted execution help apply it to your agents, tools and business rules.
The entry point
Start with a workflow review through the booking page. Confirm the agent, supported tool boundaries, evidence access and acceptance owner. Then agree the product access and blended engineering allocation in a proposal. This preview presents the proposed product experience; it is not a self-serve purchase or a commitment that every capability is available today.
The offering
Use Investigate, Evaluations, Environments and the connected evidence record. Scope the agent workflow and the result you need to establish. Retain the definitions, cases and learning as the system changes.
— One connected workspace for the reliability lifecycle
— Your sources, business expectations and acceptance owner
— Reusable checks, environments and decision history
Explore the product ↗
The FTE model
The proposed model blends AI-assisted reliability work with a defined allocation of human engineering. FTE means full-time-equivalent capacity. Agree the product access, engineer allocation, execution limits and delivery responsibility in the proposal.
— Integration and environment engineering
— Investigation, evaluation and candidate-change work
— Domain review and release authority remain explicitly owned
The result
Define the customer job, consequential failure and evidence needed to accept the result. Measure real completion and remaining human effort. Keep unmeasured benefits as hypotheses.
— Named outcome and independent acceptance evidence
— Visible coverage, exclusions and unresolved work
— A retained reliability workflow for the next release
Product artifact
Purpose
Acceptance evidence
Product artifact: Investigation and source map
Purpose: Explain the failure and its limits.
Acceptance evidence: Reviewable sources and explicit owner decisions.
Product artifact: Versioned Pack and Checks
Purpose: Protect the expected behavior on later runs.
Acceptance evidence: Validated cases and pinned definitions.
Product artifact: Environment recipe
Purpose: Reproduce relevant tools, state and failures.
Acceptance evidence: Coverage manifest and independent reset proof.
Product artifact: Tested change proposal
Purpose: Give the owner a bounded improvement to review.
Acceptance evidence: Exact revision and baseline/candidate results.
Product artifact: Outcome definition
Purpose: Know whether the customer job is completed.
Acceptance evidence: Authoritative result, membership and harm coverage.
Before the first workflow
The proposal combines product access, AI-assisted reliability execution and a defined human engineering allocation. Specify allocation, execution limits, responsibilities and acceptance evidence in the commercial scope. No universal AI-to-person replacement ratio is assumed.
Your named owner retains domain approval and release authority. Investigation confirmation, Evaluation activation, PR review and production release are separate decisions.
The customer job, source access, tool boundaries, failure cases, independent outcome evidence, engineer allocation and execution limits. Pricing and service commitments require an agreed proposal.
Start with an affected customer job, the expected result and the evidence your team would accept.
Discuss a concrete workflow ↗
AI reliability, from production to customer outcome.