Four practices. One ground truth.

We bring database-engineering rigor to probabilistic systems. Every engagement is scoped, scoped, evaluated, and handed back to you running. Pick the practice — or let us assemble the right combination.

I

AGENTIC AI

ENGAGEMENT · 12–20 wks

Agentic AI implementation

Production agents that reason over your enterprise systems — with provenance from prompt to row-level source. Built to be measured, traced, and accountable.

Multi-agent orchestration

Supervisor + specialist patterns. Routed tool-use. Graceful degradation when models fail.

Tool design

SQL, graph, doc, API. Typed contracts. Replay-safe. Cost-bounded.

Evaluation suites

Faithfulness, groundedness, refusal correctness. Offline + online. Regression-tracked.

Human-in-loop

Approval gates where the cost of being wrong is high. Audit trails on every override.

Stack we run
LangGraphCrewAIOpenAIAnthropicBedrockVertexLiteLLMHelicone

II

DATA PLATFORM

ENGAGEMENT · 12–20 wks

Data platform modernization

From legacy SQL Server estates to lakehouse, vector, and graph — a foundation your agents can stand on. Performance, governance, and bill all in scope.

Lakehouse build-out

Iceberg / Delta / Hudi. Bronze→silver→gold. Re-engineered for the agent age.

Legacy migration

SQL Server, Oracle, Teradata. Lift, refactor, retire. We literally wrote the SQL Server reference manual.

Streaming + CDC

Kafka, Debezium, Flink. Right-time analytics for agents that act, not just answer.

Cost engineering

Warehouse spend audits. Query rewrite. Materialization strategy. Average client saves 38%.

Stack we run
SnowflakeDatabricksBigQuerydbtIcebergTrinoAirflowPostgresSQL Server

III

RAG

ENGAGEMENT · 12–20 wks

Enterprise RAG

Retrieval that respects ACLs, jurisdictions, and freshness. Hybrid search, re-ranking, citation, and humans-in-the-loop where stakes demand it.

Hybrid retrieval

Dense + lexical + graph. Re-ranked. Tuned to your domain, not a generic benchmark.

ACL inheritance

Documents inherit permissions from source. No data leakage by construction, not by hope.

Citation by default

Every answer carries row-level provenance. Click any sentence, see the source.

Freshness routing

Real-time, batch, archive — routed automatically. Your CFO's questions get yesterday's data, not last quarter's.

Stack we run
pgvectorPineconeWeaviateCohere RerankNeo4jElasticVoyageOpenSearch

IV

GOVERNANCE

ENGAGEMENT · 12–20 wks

Eval, governance & AgentOps

The unsexy plumbing that lets you sleep. Tracing, replay, regression eval, cost guards — built into the system, not bolted on after an incident.

Provenance graphs

Every answer reconstructs back to inputs. Audit-ready. Regulator-ready. Lawyer-ready.

Replay & regression

Catch drift before users do. Compare model versions on real production traces.

Cost & latency guards

Per-tenant budgets. Circuit breakers. Auto-fallback to cheaper models on noncritical paths.

Compliance posture

EU AI Act, NIST AI RMF, sector-specific. Mapped to controls, not platitudes.

Stack we run
LangSmithPhoenixBraintrustHeliconeOpenTelemetryDatadog

Bring us your hardest data question.

A 45-minute discovery call with a principal engineer. No pitch deck. We'll sketch what an agentic system looks like for your stack and tell you, on the call, whether it's worth building.

Book the call →
hello@jamesbond.consulting

What we cover

● 45 min

• Map of your current data + decision surface
• Where agents add real leverage (and where they don't)
• Provenance & governance shape
• Realistic 12-week scope with budget bands

Who you'll meet

principal

A founding partner — not an SDR, not a junior associate. Three decades of database scars and four years of building agents that survive production.