The core of the platform
Creditspective preserves what your institution decided, why it decided it, and what happens next. alfa+ is the intelligence layer through which purpose-built AI agents retrieve and apply that accumulated judgment across underwriting, portfolio management and asset selection.
Decisions · rationale · terms · performance
Select a step to see what the alfa+ agent does.
Current deal documents and models become a permissioned, source-linked record.
Client-authorized APIs bring in research, ratings, market data, and internal systems.
The institution’s credit methods and relevant precedent are applied to the current deal.
Actuals, covenants, and risk signals are compared with the approved case and preserved as precedent.
Agentic AI, applied
Agents research the market against the fund’s strategy, risk profile, and return parameters, then bring relevant potential deals into view.
Agents pull the current deal, institutional memory, and approved reference data to assemble the base case, downside, rationale, and source-linked output.
Agents compare actual performance and covenants with the approved case, surface meaningful variance, and preserve the outcome for the next decision.
“Where did the downside scenarios come from?”
“Explain risk 5 in more detail.”
Human decisionThe mantle application
Creditspective sits across the institution’s existing data and workflows—preserving the systems below while applying one intelligence layer above them.
Institutional memory and credit intelligence, applied without replacing the systems below.
Enterprise controls
Select a control
Control details
Your documents are never shared with third parties.
Your data is never used to train Creditspective or third-party AI models.
Teams, roles, and workflows follow institutional policy.
Every answer links to the source document and calculation.
Creditspective was built to put one proven credit methodology behind every decision your team makes, from first screen to final workout.
Every cycle the senior team worked through stays queryable, instead of leaving with the people who lived it.
The methodology is tested against real casework, so the discipline that survives becomes your default.
Selection, underwriting, monitoring, and committee memos in one workflow, with an audit trail regulators can read.
“Choosing which deals never reach committee is where our returns are actually made. The screening discipline pays for itself in passes, not picks.”
Head of CreditDirect lending fund“Covenant drift used to surface at the quarterly review, when the options were already gone. Now it lands on the agenda while there’s still a trade to make.”
Portfolio ManagerBSL / leveraged credit“The memo the committee reads is drafted before the analyst’s second coffee, and it cites our own precedent deals back to us.”
Chief Risk OfficerCommercial banking“Your institutional memory + alfa+ = consistent, strong returns across decades of disruptive credit cycles.”
Why the core IP now carries the name of the outcome, and what the + stands for.
Why credit AI is a separate category: the research behind the platform.
What loosening documentation looks like two quarters before it prices.
The full methodology: selection, underwriting, and monitoring across cycles.
Spreads, defaults, and covenant trends. One email each month.
Creditspective is a thin intelligence layer above your current systems: spreadsheets, loan systems, data rooms, CRM.
The mantle reads the data below it and returns results: price signals, covenant alerts, and draft memos. Installation takes days.
As the margin for error shrinks, institutional memory becomes a competitive advantage. These are three primary applications across a much broader leveraged credit market.
Client data is never used to train shared models. Deploy in your own cloud, trace every number to its source cell, and hand regulators a complete audit trail.
Explore securityCalculate the effect for your team. Move the controls.
Example only: we assume 70% less time for each memo and 1,800 work hours for each analyst each year.