Data no model can trust
Customer, product and finance data live in disconnected systems with different definitions. Every AI effort starts with a cleanup nobody budgeted for.
AI & Data
AI and data consulting that reaches production and pays for itself.
Most AI projects stall on data that is not ready and pilots that never ship. We fix the data, build the agents, govern the risk, and run it for you.
- AI Readiness Assessment
- 2 to 4 weeks
- Pilot to Production
- 6 to 10 weeks
- Data Foundation Sprint
- 6 to 12 weeks
- AI Managed Services
- Monthly
Scope, timeline and deliverables agreed before work starts.
The problem
What is holding your AI back
Pilots that never ship
Proofs of concept impress in a demo and die in review because cost, accuracy and risk were never measured.
Agents with no guardrails
Teams deploy AI agents without identity, limits or monitoring, and leadership cannot answer what the agents are allowed to do.
No one owns it after launch
Once the vendor leaves, prompts drift, costs climb and nobody is watching accuracy.
What we do
Six AI and data services.
Our AI and data consulting covers the full path from strategy to operations: assessing AI readiness, building data platforms and pipelines, developing generative AI and machine learning solutions, deploying AI agents and workflow automation, and governing them responsibly. Each service can start on its own or combine into one program.
AI Strategy, Readiness & Enablement
We assess your data, systems and team, choose the use cases that will pay back, and train your people to work with AI safely.
Good fit when
You have AI ideas or scattered pilots but no agreed order to do them in, and leadership wants a plan with numbers behind it.
What you get
Talk to us about this
A ranked roadmap, a readiness report and a first use case scoped well enough to start building.
What is included
- AI opportunity mapping, with use cases ranked by payback and risk
- Data, platform and security readiness assessment
- Build, buy or partner recommendations for models and tools
- AI operating model: roles, review steps and usage policy
- Hands-on training for leaders, engineers and business teams
Data Engineering, Platforms & Analytics
Pipelines, modern data platforms, data quality and dashboards that give your business one trusted view and give AI something to learn from.
Good fit when
Reports disagree with each other, pipelines break without warning, or AI projects stall because the data is not ready.
What you get
Talk to us about this
One trusted data platform with tested pipelines, shared metrics and data your AI systems can use.
What is included
- Lakehouse and warehouse design on Snowflake, Databricks or your cloud, using open table formats such as Apache Iceberg
- Batch and streaming pipelines with automated data quality checks
- Master data, shared definitions and a governed data catalog
- Dashboards and self-service analytics in Power BI or similar tools
- Data prepared for AI: document processing, embeddings and retrieval indexes
Agentic AI & Automation
AI agents and workflow automation for the routine work your team does by hand: intake, document handling, approvals, reporting and support.
Good fit when
Teams spend hours on intake, document handling, approvals or reporting that follow a pattern but need judgement.
What you get
Talk to us about this
A production agent or automation for one workflow, with measured accuracy, cost per task and clear limits on what it may do.
What is included
- Workflow selection: where an agent beats simpler rule-based automation
- AI agents that use your systems through governed tools and connectors, including Model Context Protocol (MCP) servers
- Identity, permissions and spending limits for every agent
- Human approval steps for decisions that carry risk
- Evaluation suites, tracing and monitoring before and after go-live
Generative AI & Machine Learning
Custom models, fine-tuning, retrieval over your own knowledge, and classic machine learning for forecasting and prediction.
Good fit when
You want AI features in a product or internal tool, or better forecasts, and need to know which approach will work on your data.
What you get
Talk to us about this
A tested model or AI feature with benchmark results, running in your cloud accounts.
What is included
- Retrieval-augmented generation (RAG) over your own documents and data
- Model selection across Anthropic, OpenAI, Google, AWS and open models, tested on your tasks
- Fine-tuning and prompt engineering where they measurably help
- Classic machine learning for forecasting, scoring and anomaly detection
- Cost, latency and quality benchmarks before any model reaches users
Responsible AI & Governance
Evaluation, red-team testing, guardrails, audit trails and policy so you can prove what your AI does and prepare for regulation.
Good fit when
Customers, auditors or regulators are asking how your AI is controlled, or teams are adopting AI tools faster than policy can keep up.
What you get
Talk to us about this
A working governance process, test evidence for your key systems and documentation you can show a customer or auditor.
What is included
- AI inventory and risk classification for every system in use
- Policies and controls mapped to the EU AI Act, the NIST AI Risk Management Framework and ISO/IEC 42001
- Evaluation and red-team testing for accuracy, bias, safety and prompt injection
- Guardrails, audit trails and model documentation
- Review workflow so new AI use cases are approved quickly and consistently
AI Managed Services
We run, monitor, tune and improve the AI and automation we built for you under a monthly agreement, so results hold after launch.
Good fit when
An AI system is live and nobody on your team has the time to watch, tune and update it.
What you get
Talk to us about this
We run it for you under a monthly agreement, with response times and reporting defined in that agreement.
What is included
- Monitoring of accuracy, cost, latency and failures
- Model and prompt updates as providers release new versions
- Regular evaluation runs to catch drift before users do
- Cost control for model calls, tokens and compute
- Monthly performance report with actions taken and recommended
How we work
How we build AI differently
We measure before we build. Every engagement starts with a baseline for cost, accuracy and time saved, and we use the simplest tool that meets it. Sometimes that is an agent. Often it is rule-based automation at a fraction of the cost.
- Baseline first, then build
- Agents only where they beat simpler automation
- Evaluation suites before go-live
- Cost and accuracy monitored in production
Engagements
Ways to start, with a clear end.
Every engagement has a defined scope, duration and deliverables before work begins.
How long each engagement usually runs
ShortestLongestOngoing, monthly
AI Readiness Assessment2 to 4 weeks
Pilot to Production6 to 10 weeks
Data Foundation Sprint6 to 12 weeks
AI Managed ServicesMonthly
04 wk8 wk12 wk
AI Readiness Assessment
Deliverables
Use-case roadmap ranked by payback, data readiness report, risk and governance baseline.
Pilot to Production
Deliverables
One AI workflow taken from prototype to a monitored production system with evaluation suite and guardrails.
Data Foundation Sprint
Deliverables
Modern data platform, pipelines, quality rules and the first analytics layer.
AI Managed Services
Deliverables
Monitoring, tuning, cost control, model and prompt updates, monthly performance report.
Technology
AI and data technologies we use.
Platform-neutral. We choose based on your stack, cost and compliance needs.
Claude
OpenAI
Azure AI
AWS Bedrock
Vertex AI
LangGraph
Python
Snowflake
Databricks
dbt
Power BI
Postgres
Industries
Industries we deliver AI and data work in.
Financial Services & InsuranceDocument intelligence for underwriting and claims intake
Healthcare & Life SciencesClinical and claims data platforms with patient matching and HL7 FHIR ingestion
Retail & Consumer GoodsDemand forecasting and inventory optimization models
Software & High-TechAI feature development with evaluation suites and cost monitoring
ManufacturingPredictive maintenance models on equipment and sensor data
Logistics & Supply ChainRoute and load optimization models
Insights
All insights Related insights
AI & Data
AI agents vs workflow automation: when each one fits
Workflow automation follows steps you define. An AI agent chooses its own steps. Here is how the two differ on cost, predictability and risk, and how to decide for a…
Nov 12, 20265 min read
Financial ServicesAI model risk management in banking: what reviewers expect
US regulators replaced SR 11-7 with revised model risk guidance in April 2026. Here is what it says about AI, what model risk teams expect to see, and how to…
Nov 12, 20266 min read
AI & DataAI readiness assessment checklist: what it covers
What an AI readiness assessment looks at across use cases, data, technology, people, governance and operations, what to gather before it starts, and what the output should contain.
Nov 12, 20265 min read
Questions
Frequently asked questions
Do we need clean data before we start?
No. Assessing and fixing data is the first part of most engagements. We tell you what is ready now and what needs work before a given use case will pay back.
Will you recommend AI agents for everything?
No. We use agents where they beat simpler automation on cost and reliability. Many workflows are better served by rule-based automation, and we will say so.
How do you handle security and compliance?
Data stays in your cloud accounts. We design access, logging and guardrails from the start and align with frameworks such as the NIST AI Risk Management Framework and the EU AI Act where they apply.
What happens after launch?
Either your team takes over with our documentation and training, or we run it under AI Managed Services with monitoring, tuning and monthly reporting.
Which AI platforms do you work with?
We are platform-neutral and work across Anthropic, OpenAI, Microsoft, AWS and Google models, choosing by your existing cloud, cost and data residency needs.
Tell us what you are trying to build.
A 30-minute call is usually enough to know whether we are the right fit. We reply within one business day.