Autonomous AI Agents
& Multi-Agent Systems
We build durable, stateful autonomous agents that do not just chat — they execute complex, multi-step business workflows across your CRM, databases, browser interfaces, and internal APIs with unbreakable state recovery and transparent human-in-the-loop controls.
What We Delivered:
Autonomous Multi-Agent Loan Underwriting & Verification
Client: Commercial Lending Institution ($1.4B Loan Volume) · Commercial Banking & Lending · 6-Week Production Delivery
The Core Bottleneck
Loan officers spent 18 hours per applicant manually downloading tax returns, running KYC searches, calculating debt-service ratios, and cross-checking corporate registry records.
The ModelScale Architecture
We engineered an autonomous multi-agent graph with specialized roles: Intake Agent, Forensic Verification Agent, Financial Modeling Agent, and Credit Memo Synthesis Agent, supervised by human credit committee officers.
Key Production Components
- LangGraph stateful workflow with persistent checkpointing in PostgreSQL
- Browser-use agent automating verification lookups on state secretary-of-state portals
- Sandboxed Python execution calculating complex amortization and liquidity formulas
Production Metrics
From 14 days down to 42 minutes per loan packet
Processed 5x loan volume without adding headcount
Maintained exact credit risk thresholds over 6 months
Scope of Delivery & Architecture
Stateful Multi-Agent Orchestration
Designing collaborative agent teams with specialized responsibilities, dynamic task delegation, and centralized supervisor coordination.
Durable Execution & Checkpointing
Ensuring that if a network drops or browser crashes, the agent resumes execution from the exact prior state without repeating steps.
Tool Execution & API Integration
Equipping agents with secure capabilities to query SQL databases, send emails, trigger webhooks, and interact with web browsers.
Human-in-the-Loop (HITL) Controls
Building approval gates where agents pause execution and request human review before executing sensitive or high-financial-value actions.
Modern, Scalable Technology Foundation
- LangGraph
- Temporal.io
- CrewAI
- AutoGen
- PydanticAI
- Claude 3.5 Sonnet
- GPT-4o
- DeepSeek-R1 (Reasoning)
- Llama 3.3
- PostgreSQL Checkpoints
- Redis Event Streams
- S3 Artifact Storage
- Docker Sandboxes
- Playwright / Browser-Use
- Postman API Gateways
How We Mobilize and Deliver
Phase 1: Workflow Decomposition & Role Definition
Breaking manual processes into discrete sub-agent tasks, error conditions, and state schemas.
Phase 2: Agent Network Build & Sandbox Testing
Implementing checkpointing, tool execution, self-correction logic, and human approval gates.
Phase 3: Integration & Production Rollout
Connecting production databases, rate-limiting, audit logging, and fail-safe testing.
Transparent Engagement Tiers
Clear milestones, guaranteed IP ownership, and zero lock-in.
Single Autonomous Agent
Build an autonomous agent that handles a specific multi-step workflow with tools and human oversight.
- Stateful LangGraph implementation
- Up to 4 custom tool integrations
- Human approval interface (Slack / Web)
- Durable PostgreSQL state storage
Enterprise Multi-Agent Network
PopularCollaborative network of specialized agents orchestrating cross-departmental operations.
- Supervisor agent + up to 5 sub-agents
- Browser automation and API connectors
- Self-healing and automated error recovery
- Comprehensive admin audit dashboard
- Dedicated Lead Agent Architect
Managed Agent Pod
Continuous expansion of agent capabilities, prompt tuning, and 24/7 reliability monitoring.
- Squad of 3 Senior Agent Engineers
- Bi-weekly tool expansion and performance optimization
- Guaranteed 15-minute response SLA
Frequently Asked Questions
What prevents an autonomous agent from getting stuck in an infinite loop?
We enforce hard execution bounds, maximum step budgets, cyclical graph detection, and automated timeout triggers that gracefully escalate to a human supervisor.
Can the agent recover if our internal API goes down mid-workflow?
Yes. Because our state graphs utilize durable PostgreSQL checkpointing, the agent pauses, retries with exponential backoff, and resumes from the exact failed step once the API recovers.
How do you ensure agents do not execute dangerous actions?
We implement strict Human-in-the-Loop (HITL) authorization gates. Any action involving financial transfers, sensitive records, or customer communications pauses for explicit human sign-off.
Your next release runs on our stack.
Book a 30-minute strategy call. We'll audit one workflow, benchmark it against our best-of, and hand you a written roadmap — free.