# Reasoning agents, purpose-built for the financial stack. Pokee deploys RL-trained AI agents on your terms — on-prem, on-device, or inside your VPC — so investment, risk, and back-office teams can move at the speed of their data without ever leaving the perimeter. ## Move from chatbot demos to production agents that earn their seat at the desk. Pokee gives front-, middle-, and back-office teams the same set of primitives — research, reason, and act — wired into the systems where finance actually happens. ### Research Surface auditable answers from filings, transcripts, market data, and proprietary desks — grounded in citations your compliance team will actually accept. ### Reason Agents trained with reinforcement learning — not stitched-together prompts — to plan across long horizons, fall back gracefully, and stay within policy. ### Act Deterministic tool use across your stack — Bloomberg, OMS/EMS, ERPs, ticketing, ledgers — with full audit trails for every API call an agent makes. ## Use cases ### Workflows that compound, not chatbots that conversate. Five places Pokee agents are already replacing brittle scripts and outsourced labor inside banks, asset managers, and accounting platforms. #### Investment research & due diligence For analysts and PMs who can't afford to wait for the next analyst note. - Real-time due diligence on a target and its competitor set - Source SEC, EDGAR, and EDINET filings with summarized takeaways - Draft memos that cite primary sources, not hallucinated abstracts - Update positions overnight as filings, prints, and macro data land #### Back-office automation & journal classification Replace the offshore queue with agents that read, classify, and reconcile. - Classify journal entries, invoices, and receipts at scale - Reconcile against source ledgers with explainable mappings - Flag anomalies for human review with full document trace - Process multilingual artifacts — JP, KR, ZH, EN — in one pipeline #### Counterparty risk & fraud monitoring Synthesize structured signals and unstructured signal noise in one place. - Score counterparties using public filings, news, and proprietary feeds - Detect fraud patterns across transaction memos and ticket narratives - Generate suspicious-activity drafts with cited evidence - Adapt to new patterns via continuous RL fine-tuning, not redeploys #### Regulatory & disclosure intelligence For compliance teams shipping under the ever-shifting weight of new rules. - Monitor regulator websites and rulemaking notices in near-real-time - Map regulatory changes back to internal policies and procedures - Draft initial 10-K/10-Q narrative sections from internal data - Maintain immutable audit trails — every output traceable to source #### Operational customer service The data-sensitive support work generic LLMs simply cannot touch. - Equip agents with PII-aware copilots that handle escalations - Auto-summarize each customer relationship before every interaction - Resolve account disputes with policy-grounded responses - Route complex cases with full context — never start from zero ## The reasoning core that lets one GPU hold an entire client relationship. The Pokee Engine is our proprietary inference architecture — a black box for now — that pushes context windows past ten million tokens on a single GPU. No chunking, no retrieval gymnastics, no lossy summaries. The whole portfolio fits in memory. ### Context - 1786M+ tokens ### Footprint - 178 GPU ### Latency Sub-sectool call ### Training RLnative ## Verified, not vibes FinanceBench is the industry-standard evaluation built on 150+ real 10-Ks, 10-Qs, and earnings transcripts. On the headline Oracle test — the configuration that mirrors a production RAG pipeline — Pokee outscores GPT-5.4 outright. ### Benchmark FinanceBench - Corpus: 150+ filings & transcripts - Comparison: Pokee vs. GPT-5.4 - Evaluation date: Q1 2026, internal - Winner: Headline · Oracle accuracy On the Oracle test — where the model is given the relevant document and must extract, compute, and reason — Pokee edges out the frontier model by **+0.4 points**. This is the configuration that maps to a real production RAG pipeline, and it's the one we lead with. ## Built for the regulated stack Pokee was designed from day zero to live behind your firewall. We don't ship a SaaS that pretends to be enterprise — we ship infrastructure your security team can actually own. ### Privately deployable Run inside your VPC, on-prem datacenter, or directly on workstation silicon. Weights and data never leave your perimeter. ### Regulator-ready Every agent action is logged, traceable, and replayable. Built-in usage monitoring, output auditing, and policy guardrails. ### Fully customizable Fine-tune on your tickets, memos, and ledgers. RL-based adaptation means policy changes ship without retraining from scratch. ### Forward-deployed Pokee engineers embed with your team for the first deployment. We ship to production — not slides — inside the first quarter. ## Move your AI roadmap from pilot to production. Connect with our team to scope an agent that fits your stack, your data, and your regulator's appetite for risk. ### Deployment & Governance #### Private deployment A dedicated managed tenant, your own VPC on AWS, Azure or GCP, on premises, or air-gapped. Your data never leaves your boundary. #### Approvals and audit Approval gates wherever you set them, role-based access, and a full audit log. Every agent action is attributable and reviewable. #### Measurable pilots Pilots run on two or three real workflows, typically live inside two weeks. Measure time saved, accuracy and cycle time before rollout.