AI Development
Production AI applications, agentic systems, LLM fine-tuning, and data pipelines — built by the team that published research on AI agent design and trained LLMs from scratch. We understand EU AI Act requirements, training data copyright, and model governance well enough to get it right the first time.
Open-source NLP libraries used across the legal industry (LexNLP), benchmark datasets with 422+ citations (LexGLUE), and production AI systems shipped for Fortune 500 companies. The same team that audits AI can build it — or fix it.
Starting at $30K | 4-24 weeks
Services
AI Application Development
Production AI applications from proof-of-concept through deployment. Compliance controls embedded throughout — not added after launch.
4-16 weeks
AI Agent Design & Implementation
Agentic AI systems for law, finance, and professional services. Architecture grounded in published agent design research (2025).
4-12 weeks
LLM Fine-Tuning & Custom Models
Domain-specific models trained on your data with copyright-clean methodology. Evaluation, benchmarking, and deployment included.
4-12 weeks
Data Pipeline & Infrastructure
Data ingestion, processing, and serving infrastructure for AI workloads. DataOps, quality and observability, ML training pipelines.
4-12 weeks
Compliance-by-Design Development
Security, privacy, and AI governance controls built into the architecture from sprint one. EU AI Act, NIST AI RMF, and industry-specific requirements.
Ongoing
Legacy System Modernization
AI-accelerated assessment and migration of legacy systems. Code analysis, architecture redesign, and incremental migration with minimal disruption.
8-24 weeks
Why us
We've built LLMs from scratch
KL3M wasn't fine-tuning on top of someone else's model. It was training from scratch — 132M+ documents, custom tokenizers, domain-specific architecture, copyright-clean data, Fairly Trained certification. When we build AI for you, it's backed by that level of technical depth.
Compliance is built in, not bolted on
Most development shops treat compliance as someone else's problem. We hold CPA, dual CIPP, and Certified AI Auditor credentials — the same team that writes the code understands the regulatory requirements. Security controls, privacy protections, and AI governance are part of the architecture from sprint one.
Published research on agent design
Our 2025 papers "How to Design an AI Agent" and "Governing AI Agents" aren't whitepapers — they're published research on agent architectures, protocols, and governance. When we build agentic systems, the design decisions are grounded in published, cited work.
Why licens.io?
| Big 4 | licens.io | |
|---|---|---|
| AI depth | Wrapper around vendor APIs | Built LLMs from scratch: KL3M |
| Compliance | Bolted on after | Built in from sprint one |
| Agent design | Ad hoc engineering | Peer-reviewed research, 2025 |
| Open source | Proprietary only | LexNLP, LexGLUE: 524 citations |
| Scale | Startup-stage | AmLaw 50, Fortune 500 clients |
| Pricing | Hourly, $150-250/hr | Fixed-fee, $30K-$300K |
AI depth
Big 4
Wrapper around vendor APIs
licens.io
Built LLMs from scratch: KL3M
Compliance
Big 4
Bolted on after
licens.io
Built in from sprint one
Agent design
Big 4
Ad hoc engineering
licens.io
Peer-reviewed research, 2025
Open source
Big 4
Proprietary only
licens.io
LexNLP, LexGLUE: 524 citations
Scale
Big 4
Startup-stage
licens.io
AmLaw 50, Fortune 500 clients
Pricing
Big 4
Hourly, $150-250/hr
licens.io
Fixed-fee, $30K-$300K
Who this is for
- ✓ Enterprises needing production AI with compliance requirements met from day one, not retrofitted later
- ✓ PE/VC portfolio companies building AI capabilities across their holdings
- ✓ Regulated industries (finance, healthcare, legal) where AI systems must satisfy compliance requirements from architecture through deployment
- ✓ Companies needing agentic AI systems designed with governance and accountability built in
- ✓ Organizations modernizing legacy systems that need AI-accelerated migration without disruption
Frequently asked questions
How is your AI development different from a typical dev shop?
We integrate regulatory and compliance requirements into the architecture from the start. The same firm that builds your AI system can audit it, govern it, and defend it in front of regulators. CPA, CIPP, and Certified AI Auditor credentials — no handoff between the team that builds and the team that certifies.
How much does custom AI development cost?
AI application development typically runs $50K-$250K depending on scope. LLM fine-tuning is $40K-$150K. Data pipeline builds are $30K-$100K. All quoted as fixed-fee engagements with defined deliverables.
Should I build or buy an AI agent?
It depends on how central the agent is to your business, how sensitive the data is, and what regulatory requirements apply. If your use case involves regulated processes, proprietary data, or differentiated workflows, building gives you more control. We help you make that assessment grounded in our published agent design research.
Can you fine-tune on our proprietary data?
Yes. We fine-tune and train models on client data with strict data handling protocols. Our experience with KL3M's copyright-clean data pipeline means we understand data provenance, licensing, and governance throughout the training process.
What is compliance-by-design?
Regulatory requirements — EU AI Act, NIST AI RMF, industry-specific rules — built into the system architecture, data flows, and deployment pipeline from the beginning. Access controls, audit logging, data lineage, and model documentation are part of the design, not a post-launch remediation project.
How long does a typical engagement take?
Data pipeline builds run 4-12 weeks. AI application development takes 4-16 weeks. Legacy modernization runs 8-24 weeks. Each engagement is scoped with clear milestones and deliverables upfront.
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