CurrentAI's intelligent Excel agent automatically updates your models in real-time, while traditional model update services rely on slow, manual processes requiring extensive restructuring.
Approach
Automated AI intelligence vs manual human labor
Purpose-built AI agent that deeply understands your existing model structure, automatically updating data in real-time as earnings and events occur. No restructuring required.
Automated real-time updates as data becomes available
Understands your existing model logic and structure
No special formatting or tagging required
Updates all models simultaneously
Custom-tuned for reliability and accuracy
Instant deployment to existing models
Human analysts manually input data into models, requiring deep restructuring of your existing files to match their standardized format. Slow turnaround with dependency on manual labor.
Manual data entry by offshore teams
Requires complete model restructuring
Deep formatting and standardization needed
Slow turnaround times (hours to days)
One model at a time processing
Ongoing restructuring as models evolve
Capabilities
How each solution handles Excel model updates
Intelligent agent that works with your models as-is
Human-powered data entry requiring standardization
Comparison
Direct comparison of capabilities and requirements
| Feature | Current AI | Traditional Services |
|---|---|---|
| Update Speed | Real-time (seconds after earnings) | Hours to days after release |
| Model Restructuring | None required—works with your structure | Complete restructuring mandatory |
| Onboarding Time | Instant—agent learns your model | Weeks of reformatting and standardization |
| Scalability | Unlimited models updated simultaneously | Limited by manual labor capacity |
| Process | Fully automated AI agent | Manual outsourced data entry |
| Formatting Requirements | No special formatting needed | Strict standardization required |
| Model Logic Understanding | Deep comprehension of your calculations | Basic data input to predefined cells |
| Cost Structure | Per-model agent deployment | Per-update labor costs |
| Accuracy | AI-validated with consistency checks | Human entry with potential errors |
| Maintenance | Agent adapts to model changes | Re-restructuring when models evolve |
Deep Dive
What makes each approach unique
Zero restructuring required. CurrentAI's agent deeply understands your existing model structure, formulas, and logic. It integrates seamlessly without any reformatting, tagging, or standardization.
Requires complete model restructuring to match the service provider's standardized format. Every model must be reformatted, with ongoing maintenance as your models evolve.
Instant deployment. The agent analyzes your model structure and begins real-time updates immediately. Updates flow within seconds of earnings releases.
Weeks of onboarding per model. Each model must be manually restructured, mapped, and standardized before the first update can occur.
Real-time automated updates. The moment earnings data is released, the agent processes and updates all relevant models simultaneously, often before you've finished reading the transcript.
Manual processing delay. Offshore teams manually enter data after earnings calls, resulting in hour-to-day delays. Peak earnings season creates significant backlogs.
Works with any model structure. Whether you use custom layouts, complex formulas, or unique methodologies, the agent adapts to your approach without constraints.
Limited to standardized formats. Models must conform to the service provider's predefined structure, limiting your ability to use custom modeling approaches.
Unlimited parallel processing. Deploy agents across hundreds of models simultaneously. Each model gets real-time updates without any performance degradation.
Manual labor bottleneck. Scaling requires proportionally more outsourced labor. Each new model adds to processing time and costs.
Deep comprehension of model logic. The agent understands your calculation chains, dependencies, and business logic, ensuring updates respect your modeling methodology.
Basic data entry into cells. Manual input focuses on populating specific cells without understanding broader model logic or calculation flows.
Use Cases
How each solution performs in actual model update situations
Analyst builds custom NVDA model with proprietary revenue breakdown structure and wants automated updates starting with next earnings.
Deploy Excel agent to the model. Agent analyzes structure, identifies data inputs, and maps earnings data flows. First automated update ready for next earnings call—total time: 5 minutes.
Submit model to service provider. Reformat model to match their standardized template, including all schedules and assumptions. Map custom calculations to standard format. Weeks of back-and-forth restructuring before first update.
CurrentAI enables instant deployment with zero restructuring. Traditional services require weeks of reformatting and force abandonment of custom model structure.
20 portfolio company earnings released Tuesday 4-6pm. Models need updates for Wednesday morning portfolio review.
Agents automatically update all 20 models in real-time as each company reports. By 6:30pm, all models reflect latest earnings. Analyst reviews updated models Wednesday morning.
Submit update requests to service provider. Offshore team processes updates sequentially through the night. 12-15 models completed by Wednesday morning. Remaining 5-8 models updated throughout the day.
CurrentAI delivers 100% completion by market open. Traditional services' manual process leaves critical models outdated during morning review.
Firm updates revenue model methodology for SaaS companies, changing from quarterly to segment-level recognition with new breakdown structure.
Update model structure as desired. Agent automatically recognizes new layout, adapts to new revenue segments, and continues automated updates without interruption.
Model changes break the service provider's standardized mapping. Must resubmit model for complete re-restructuring. Multi-week delay while model is remapped to standard format. May need to compromise on new structure to fit standard template.
CurrentAI adapts instantly to model evolution. Traditional services require full re-onboarding and may force compromise on preferred model structure.
Fund expands coverage from 50 to 80 companies. Need all 80 models receiving automated updates within one week.
Deploy agents to 30 new models. Each model analyzed and ready for automated updates within minutes. All 80 models receiving real-time updates by end of week.
Submit 30 new models to service provider. With manual restructuring bottleneck, process 3-5 models per week. Full coverage achieved in 6-10 weeks. Requires significant restructuring effort for each model.
CurrentAI enables rapid coverage expansion without restructuring. Traditional services' manual process makes scaling prohibitively slow.
Analyst uses proprietary DCF model with custom WACC calculations and non-standard terminal value approach. Needs automated updates while preserving methodology.
Agent understands custom formula logic and calculation dependencies. Automatically updates input data while preserving all proprietary calculations and methodologies. Custom structure fully maintained.
Custom model structure incompatible with traditional service provider's standardized format. Must either: (1) Abandon proprietary methodology to use their standard DCF, or (2) Maintain custom model manually without automated updates.
CurrentAI preserves proprietary methodologies with full automation. Traditional services force choice between standardization or manual updates.
Join leading investment firms who've eliminated manual model updates and restructuring burdens. CurrentAI's Excel agent delivers real-time updates to your existing models without any reformatting.
