Identity Transformation Force · Context decides. Not policy.
One decision brain for every human, machine and AI agent.
Every access request by every identity is decided, bounded and explainable by one engine you control. Blast radius is known before the incident, revocation propagates to every connected system at once, and no model sits in the decision path.
Four decisions no policy engine can make
Every agent acts on authority delegated from someone. At the moment it reaches for data, a tool or production, should this actor, with this authority, at this risk, be allowed — and how much? No policy engine can answer, because nobody wrote the policy. ConteXengine, from Identity Transformation Force, computes it.
Computed, not authored
Risk, compliance and trust models fuse signals from your whole estate into one score per decision. Others evaluate policies someone wrote. ConteXengine computes what no one had to write.
Runtime graph reasoning
Delegation chains attenuated hop by hop, effective access computed live, blast radius answered in the request path, not in an after-the-fact report.
One brain, three populations
Humans, AI agents and machine identities share one decision intelligence, one posture and one audit trail. No agent ever exceeds the human it represents.
Explainable provenance
Every permit, deny and step-up carries its graph path: who, why, weighted by what risk and trust. Auditors see reasoning, not just logs.
What you never have to do again
The policy project ends here.
Every access tool you own waits for someone to write the rule, own the rule and defend the rule when it goes wrong. ConteXengine computes the decision instead, from the authorization you already run and what is true right now.
Months authoring roles, attributes and rules for every system, then re-authoring them when the business changes.
Roles, attributes, policies and entitlements you already have are inputs. Eligibility is computed per request. Nothing new to write.
Security wrote it, the app team changed it, the auditor can’t tell who approved the version that failed. The ownership drama never ends.
Every decision carries its reasoning and its version. Teams tune outcomes and review evidence instead of arguing over rule text.
A JIT product for people, an NHI product for keys, a gateway for agents, each with its own policies, scores and audit trail.
People, service accounts and AI agents decided by the same engine, scored on the same contract, proven in one ledger.
Grants accumulate between reviews; the review certifies what nobody dares to remove.
Access is held only as long as the context justifies it and pulled back mid-session the moment it doesn’t.
Logs from five systems, three teams interviewed, a narrative nobody can fully verify.
Each decision was recorded with its provenance the moment it was made. Pick a framework, export the evidence.
Why now
Three things changed at once.
Agents outnumber people
Every team is standing up agents that hold credentials, call tools and delegate to other agents. The authority they run on was never computed by anyone.
Regulators ask why, not what
Examiners now want the reason a specific access was allowed, with evidence. Logs describe what happened; nothing on the market records the decision.
Standing privilege is the breach
The access granted years ago and never re-decided is what attackers inherit. Policy projects have not removed it; computing eligibility per request does.
Nine problems, at a glance
Nine questions you can’t answer today. Pick yours.
Each card is a question a board, an examiner or an architect will ask. Open it for the answer, the walkthrough and the detail.
See it work · Identity Transformation Force
Zero standing privilege, decided per request.
In this walkthrough a privileged request is validated against its change ticket, evaluated against live context, granted for one hour and scoped to the ticket. The same request without a valid ticket is denied with the reason in plain language, and both decisions land on the ledger with their policy versions stamped.
One decision point for every tool you run.
Complement, never replace. The tools you own, and the ones you add next, consult one decision point for every actor.
Every actor
People, service accounts, AI agents and machines ask for access.
Your enforcement points
SSO, PAM, governance, AI and MCP gateways and RAG pipelines, today and as you add more.
ConteXengine
Context graph, risk, compliance and trust decide each request.
A scoped grant
Just enough access, for just long enough, revoked the moment context changes, with the reason recorded.
How it deploys
Control plane in our cloud. Data plane inside yours.
The multi-tenant control plane handles licensing, releases and context-model templates. The data plane — your graph, your signals, your decisions — runs inside your boundary, including isolated networks. No customer data leaves it, which is why third-party security reviews move quickly.
Models help us build and tune. Every live verdict is deterministic and replayable; no AI model sits in the decision path.
Your first thirty days
- Connect, read-only. Directories, cloud IAM, data platforms and logs in shadow mode. Nothing is enforced.
- See your verdicts. Every request ConteXengine would have decided on your real traffic, with the reason, plus the ranked inventory of standing privilege and ownerless identities.
- Decide. Keep the evidence pack and the plan either way. Turn on enforcement for the two problems that cost you most.
Nine problems. One decision layer.
Three you already budget for. Three nobody has a line item for yet. Three that belong to the Chief AI Officer and the Chief Data Officer. Identity Transformation Force decides all nine with the same engine.
Use case 1 of 9 · CISO / Head of IAM
Standing privilege goes to zero. The CISO stops owning a breach that was pre-authorized years ago.
Every large enterprise runs on access that was granted once and never re-decided. ConteXengine computes eligibility per request, so there is no standing role to find and no timer to maintain.
The problem
- Granted once, never re-decidedAdmin keys, roles and tokens issued years ago are still live tonight, with no expiry and no owner watching.
- One JIT tool per populationEvery just-in-time product covers one kind of identity and brings its own timer. Nobody can say which standing keys could reach the crown jewels.
What changes
- Decided, not storedEligibility is computed at the moment access happens — not stored in a role that a directory, a PAM vault and a governance platform all agree is fine.
- One engine, three populationsThe same graph and the same signals decide a person, a payroll service account and a copilot. Not another JIT tool for one more population.
Use case 2 of 9 · CISO / Head of IAM
Every service account gets an owner, a score and an expiry. The “nobody knows what breaks” excuse is gone.
Most estates have more service accounts than people, and most of those have no named owner. ConteXengine discovers them from real evidence, scores them like any other identity, and converts the static key into a just-in-time role.
The problem
- They accumulatedA migration here, a vendor integration there, a script someone wrote on a Friday. Nobody created them on purpose; nobody answers for them now.
- Admin reach, no expiryService accounts with standing Domain Admin rights and passwords that never expire stay live because nobody knows what breaks.
What changes
- Not a bolted-on moduleOne record type, one score, one engine for humans, machines and agents. Ownership, reach and findings feed the same decision.
- Converted, not reportedThe playbook changes what the key can do, and the re-import confirms it. The finding closes.
Use case 3 of 9 · CISO / GRC and audit
“Why was this allowed?” is answered in one click. Audit stops being a six-week project.
When an examiner asks what an identity could reach and why, the honest answer in most enterprises is a six-week reconstruction. ConteXengine records every access decision with its causal chain, sealed with the policy versions in force.
The problem
- No system holds the joinIdentity, data platforms and pipelines each know a piece. Pulling logs from five systems and interviewing three teams produces a narrative nobody can fully verify.
- Logs say what, never whyAttestation happens per policy, not per decision. The evidence isn't missing; it was never recorded as a decision.
What changes
- Dashboard, rollup and export are the same rowsOne ledger behind every surface, so they always agree.
- A record of why, not a log of whatVerdict, reason, scores, signals and versions on every decision, for people, agents and machines.
Use case 4 of 9 · Chief AI Officer / CISO
No agent exceeds the human it works for — at hop one or hop four. The Chief AI Officer ships without a security veto.
Agents hand work to agents to tools, three and four hops deep, and the last hop runs with whatever authority leaked down the chain. ConteXengine recomputes effective scope on every call and bounds it by the human the chain works for.
The problem
- Delegation chains are routineAgents calling sub-agents calling tools. Nobody computes what the last hop is actually allowed to do.
- First-hop checks are a checkboxThe market checks the first call and stops. The chain is the exposure.
What changes
- Past hop oneScope is recomputed beyond the first call — the capability the field and the standards bodies have not solved.
- The graph is the chainNo policy describes the chain; the delegation graph is the chain, and the ceiling is a person.
Use case 5 of 9 · Chief AI Officer / Chief Data Officer
Copilots answer per person, per chunk. The CFO’s data never reaches the contractor’s screen.
Content is indexed once, for all askers, so your lowest-cleared contractor and your CFO get the same restricted detail from the same question. ConteXengine attaches classification and lineage before anything enters an index, and decides retrieval per asker.
The problem
- The index doesn't know who's askingChunked once, served to everyone. The leak isn't a misconfiguration; it's how the index was built.
- Retrieval-time filters can't fix admissionIf classification never entered the index, nothing downstream can enforce it.
What changes
- Live, not scriptedA single label difference in the graph drives the whole contrast.
- Fails closedThe unmapped element stays dark; it never gets invented.
Use case 6 of 9 · Security operations / CISO
Containment in seconds, across connected apps. Security operations stops waiting for a token to expire.
A compromise is flagged in one app while the same session keeps working in the other six until the next token refresh. ConteXengine collapses trust on evidence and ends the grant in every connected application, out of band.
The problem
- Flagged in one appThe guardrail catches the injection where it happened. The user's other sessions keep serving the stale, still-trusted answer.
- A kill switch that isn't an architectureMost are a button on one surface. Recovery is a reset nobody can audit.
What changes
- It falls out of the graphThe engine already knows the agent's full reach across every app; containment doesn't have to be wired per application.
- Out of bandEnforced at the apps and the vault, not by asking the agent to stop.
Use case 7 of 9 · Chief AI Officer
Every AI agent becomes a governed identity. The Chief AI Officer can say yes to the next hundred.
Each one holds credentials, calls tools and hands work to other agents — and almost none is an identity anyone governs. ConteXengine discovers every agent, gives it an owner, a score and a known reach, bounds it at runtime and proves every call.
The problem
- Ungoverned by defaultAgents are created faster than anyone registers them, with credentials that never expire.
- Authority by inheritanceAn agent runs with whatever its chain passed down. Nobody computed it.
What changes
- Above every platformSits above agent platforms, copilots and homegrown chains as the authorization call they make.
- One lifecycle, one graphAgents, people and machine identities are decided by the same engine.
Use case 8 of 9 · CISO / GRC and audit / MSSPs and advisors
Identity exposure, ranked and acted on. The CISO hands the board a plan, not a posture report.
A read-only, shadow-mode engagement produces a risk profile of every identity in scope, the problems ranked by blast radius, and a remediation plan — and a shared-signals hub turns findings into actions across your identity providers and applications.
The problem
- Posture without consequenceReports describe the problem and open tickets. Nothing changes what an identity can do tonight.
- Three populations, three reportsPeople, machine identities and agents are assessed by different tools with different scores.
What changes
- One report, three populationsPeople, keys and agents scored on the same contract.
- Actions, not ticketsSeventeen built-in actions run where they're supported — disable, revoke sessions, rotate credential, remove access.
Use case 9 of 9 · Chief Data Officer / Chief AI Officer
The data lake finally has an authorization model. The Chief Data Officer can breathe easy.
Who may see the data, and how sensitive it is, are both set at the source — and both are lost the moment data enters a pipeline. ConteXengine carries authorization, classification and lineage into the graph and decides per asker, per column, per chunk.
The problem
- Lost in the pipelineBy the time data reaches the lake and the index, nobody can say who may see which column.
- So everyone can, or nobody canAccess is either open or locked, and both are wrong.
What changes
- Lineage in the verdictClassification travels with lineage, so the label at retrieval is the label set at the source. Patent pending.
- Never inventedAn element no source can map stays dark. The engine never guesses an authorization.
Who wins on day one
Identity Transformation Force built ConteXengine for the people who have to answer for access — and for the ones who have to move fast anyway.
Stop writing policies and start owning outcomes.
- The context graph assembles itself from the systems you already run, every identity gets a computed verdict at the moment of access, and standing privilege retires through the vault and PAM you already own.
- Your team tunes decisions instead of authoring rules.
Ship agents at the speed the business wants, with proof the risk committee will accept.
- Every agent acts under the ceiling of the person it represents, authority can only shrink down a chain, and a misbehaving agent is contained in seconds.
- AI adoption stops waiting on security sign-off.
Every decision reaches the data element.
- Who, and which agent, can touch the cardholder table, the exec-comp view or the patient record is answered live, in the request path, and enforced there, with classification and lineage carried into every verdict.
- Governance becomes a runtime control, not a quarterly report.
One answer for the board: every action by every human, machine and agent is decided, bounded and explainable by one brain you control.
- Blast radius is known before the incident, revocation propagates to every connected system at once, and nothing in the decision path is a model that can be manipulated.
One verdict API instead of authorization code in every app and agent.
- Ask before the tool call, get a scoped answer in milliseconds, and pass security review the first time, because the reasoning ships with the decision.
Evidence an examiner can read, not logs to excavate.
- Every decision carries its provenance and its SOX, HIPAA, PCI-DSS or GDPR mapping; an injection or anomaly signal becomes an instant scope-down or revocation, everywhere at once, and the whole sequence replays.
Give every identity exactly the authority its risk earns. Take it back the instant that risk changes. Prove both.
Runs in your environment
Deployed inside your boundary, including isolated networks. Your data stays where it is.
No AI in the decision path
Models help us build and tune. Every live verdict is deterministic and replayable.
Built and run with you
A build partner connects your estate, then a 24×7 global command center runs it with you.
Patent pending
A new approach to runtime authorization for the agentic enterprise.